Search results for: watershed algorithm
3214 Intelligent Minimal Allocation of Capacitors in Distribution Networks Using Genetic Algorithm
Authors: S. Neelima, P. S. Subramanyam
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A distribution system is an interface between the bulk power system and the consumers. Among these systems, radial distributions system is popular because of low cost and simple design. In distribution systems, the voltages at buses reduces when moved away from the substation, also the losses are high. The reason for a decrease in voltage and high losses is the insufficient amount of reactive power, which can be provided by the shunt capacitors. But the placement of the capacitor with an appropriate size is always a challenge. Thus, the optimal capacitor placement problem is to determine the location and size of capacitors to be placed in distribution networks in an efficient way to reduce the power losses and improve the voltage profile of the system. For this purpose, in this paper, two stage methodologies are used. In the first stage, the load flow of pre-compensated distribution system is carried out using ‘dimension reducing distribution load flow algorithm (DRDLFA)’. On the basis of this load flow the potential locations of compensation are computed. In the second stage, Genetic Algorithm (GA) technique is used to determine the optimal location and size of the capacitors such that the cost of the energy loss and capacitor cost to be a minimum. The above method is tested on IEEE 9 and 34 bus system and compared with other methods in the literature.Keywords: dimension reducing distribution load flow algorithm, DRDLFA, genetic algorithm, electrical distribution network, optimal capacitors placement, voltage profile improvement, loss reduction
Procedia PDF Downloads 3853213 An Efficient Machine Learning Model to Detect Metastatic Cancer in Pathology Scans Using Principal Component Analysis Algorithm, Genetic Algorithm, and Classification Algorithms
Authors: Bliss Singhal
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Machine learning (ML) is a branch of Artificial Intelligence (AI) where computers analyze data and find patterns in the data. The study focuses on the detection of metastatic cancer using ML. Metastatic cancer is the stage where cancer has spread to other parts of the body and is the cause of approximately 90% of cancer-related deaths. Normally, pathologists spend hours each day to manually classifying whether tumors are benign or malignant. This tedious task contributes to mislabeling metastasis being over 60% of the time and emphasizes the importance of being aware of human error and other inefficiencies. ML is a good candidate to improve the correct identification of metastatic cancer, saving thousands of lives and can also improve the speed and efficiency of the process, thereby taking fewer resources and time. So far, the deep learning methodology of AI has been used in research to detect cancer. This study is a novel approach to determining the potential of using preprocessing algorithms combined with classification algorithms in detecting metastatic cancer. The study used two preprocessing algorithms: principal component analysis (PCA) and the genetic algorithm, to reduce the dimensionality of the dataset and then used three classification algorithms: logistic regression, decision tree classifier, and k-nearest neighbors to detect metastatic cancer in the pathology scans. The highest accuracy of 71.14% was produced by the ML pipeline comprising of PCA, the genetic algorithm, and the k-nearest neighbor algorithm, suggesting that preprocessing and classification algorithms have great potential for detecting metastatic cancer.Keywords: breast cancer, principal component analysis, genetic algorithm, k-nearest neighbors, decision tree classifier, logistic regression
Procedia PDF Downloads 753212 Using Maximization Entropy in Developing a Filipino Phonetically Balanced Wordlist for a Phoneme-Level Speech Recognition System
Authors: John Lorenzo Bautista, Yoon-Joong Kim
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In this paper, a set of Filipino Phonetically Balanced Word list consisting of 250 words (PBW250) were constructed for a phoneme-level ASR system for the Filipino language. The Entropy Maximization is used to obtain phonological balance in the list. Entropy of phonemes in a word is maximized, providing an optimal balance in each word’s phonological distribution using the Add-Delete Method (PBW algorithm) and is compared to the modified PBW algorithm implemented in a dynamic algorithm approach to obtain optimization. The gained entropy score of 4.2791 and 4.2902 for the PBW and modified algorithm respectively. The PBW250 was recorded by 40 respondents, each with 2 sets data. Recordings from 30 respondents were trained to produce an acoustic model that were tested using recordings from 10 respondents using the HMM Toolkit (HTK). The results of test gave the maximum accuracy rate of 97.77% for a speaker dependent test and 89.36% for a speaker independent test.Keywords: entropy maximization, Filipino language, Hidden Markov Model, phonetically balanced words, speech recognition
Procedia PDF Downloads 4523211 Multiloop Fractional Order PID Controller Tuned Using Cuckoo Algorithm for Two Interacting Conical Tank Process
Authors: U. Sabura Banu, S. K. Lakshmanaprabu
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The improvement of meta-heuristic algorithm encourages control engineer to design an optimal controller for industrial process. Most real-world industrial processes are non-linear multivariable process with high interaction. Even in sub-process unit, thousands of loops are available mostly interacting in nature. Optimal controller design for such process are still challenging task. Closed loop controller design by multiloop PID involves a tedious procedure by performing interaction study and then PID auto-tuning the loop with higher interaction. Finally, detuning the controller to accommodate the effects of the other process variables. Fractional order PID controllers are replacing integer order PID controllers recently. Design of Multiloop Fractional Order (MFO) PID controller is still more complicated. Cuckoo algorithm, a swarm intelligence technique is used to optimally tune the MFO PID controller with easiness minimizing Integral Time Absolute Error. The closed loop performance is tested under servo, regulatory and servo-regulatory conditions.Keywords: Cuckoo algorithm, mutliloop fractional order PID controller, two Interacting conical tank process
Procedia PDF Downloads 4943210 Renewable Integration Algorithm to Compensate Photovoltaic Power Using Battery Energy Storage System
Authors: Hyung Joo Lee, Jin Young Choi, Gun Soo Park, Kyo Sun Oh, Dong Jun Won
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The fluctuation of the output of the renewable generator caused by weather conditions must be mitigated because it imposes strain on the system and adversely affects power quality. In this paper, we focus on mitigating the output fluctuation of the photovoltaic (PV) using battery energy storage system (BESS). To satisfy tight conditions of system, proposed algorithm is developed. This algorithm focuses on adjusting the integrated output curve considering state of capacity (SOC) of the battery. In this paper, the simulation model is PSCAD / EMTDC software. SOC of the battery and the overall output curve are shown using the simulation results. We also considered losses and battery efficiency.Keywords: photovoltaic generation, battery energy storage system, renewable integration, power smoothing
Procedia PDF Downloads 2763209 Optimization of FGM Sandwich Beams Using Imperialist Competitive Algorithm
Authors: Saeed Kamarian, Mahmoud Shakeri
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Sandwich structures are used in a variety of engineering applications including aircraft, construction and transportation where strong, stiff and light structures are required. In this paper, frequency maximization of Functionally Graded Sandwich (FGS) beams resting on Pasternak foundations is investigated. A generalized power-law distribution with four parameters is considered for material distribution through the thicknesses of face layers. Since the search space is large, the optimization processes becomes so complicated and too much time consuming. Thus a novel meta–heuristic called Imperialist Competitive Algorithm (ICA) which is a socio-politically motivated global search strategy is implemented to improve the speed of optimization process. Results show the success of applying ICA for engineering problems especially for design optimization of FGM sandwich beams.Keywords: sandwich beam, functionally graded materials, optimization, imperialist competitive algorithm
Procedia PDF Downloads 5563208 An Introductory Study on Optimization Algorithm for Movable Sensor Network-Based Odor Source Localization
Authors: Yossiri Ariyakul, Piyakiat Insom, Poonyawat Sangiamkulthavorn, Takamichi Nakamoto
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In this paper, the method of optimization algorithm for sensor network comprised of movable sensor nodes which can be used for odor source localization was proposed. A sensor node is composed of an odor sensor, an anemometer, and a wireless communication module. The odor intensity measured from the sensor nodes are sent to the processor to perform the localization based on optimization algorithm by which the odor source localization map is obtained as a result. The map can represent the exact position of the odor source or show the direction toward it remotely. The proposed method was experimentally validated by creating the odor source localization map using three, four, and five sensor nodes in which the accuracy to predict the position of the odor source can be observed.Keywords: odor sensor, odor source localization, optimization, sensor network
Procedia PDF Downloads 2953207 Automated Digital Mammogram Segmentation Using Dispersed Region Growing and Pectoral Muscle Sliding Window Algorithm
Authors: Ayush Shrivastava, Arpit Chaudhary, Devang Kulshreshtha, Vibhav Prakash Singh, Rajeev Srivastava
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Early diagnosis of breast cancer can improve the survival rate by detecting cancer at an early stage. Breast region segmentation is an essential step in the analysis of digital mammograms. Accurate image segmentation leads to better detection of cancer. It aims at separating out Region of Interest (ROI) from rest of the image. The procedure begins with removal of labels, annotations and tags from the mammographic image using morphological opening method. Pectoral Muscle Sliding Window Algorithm (PMSWA) is used for removal of pectoral muscle from mammograms which is necessary as the intensity values of pectoral muscles are similar to that of ROI which makes it difficult to separate out. After removing the pectoral muscle, Dispersed Region Growing Algorithm (DRGA) is used for segmentation of mammogram which disperses seeds in different regions instead of a single bright region. To demonstrate the validity of our segmentation method, 322 mammographic images from Mammographic Image Analysis Society (MIAS) database are used. The dataset contains medio-lateral oblique (MLO) view of mammograms. Experimental results on MIAS dataset show the effectiveness of our proposed method.Keywords: CAD, dispersed region growing algorithm (DRGA), image segmentation, mammography, pectoral muscle sliding window algorithm (PMSWA)
Procedia PDF Downloads 3063206 Dimension Free Rigid Point Set Registration in Linear Time
Authors: Jianqin Qu
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This paper proposes a rigid point set matching algorithm in arbitrary dimensions based on the idea of symmetric covariant function. A group of functions of the points in the set are formulated using rigid invariants. Each of these functions computes a pair of correspondence from the given point set. Then the computed correspondences are used to recover the unknown rigid transform parameters. Each computed point can be geometrically interpreted as the weighted mean center of the point set. The algorithm is compact, fast, and dimension free without any optimization process. It either computes the desired transform for noiseless data in linear time, or fails quickly in exceptional cases. Experimental results for synthetic data and 2D/3D real data are provided, which demonstrate potential applications of the algorithm to a wide range of problems.Keywords: covariant point, point matching, dimension free, rigid registration
Procedia PDF Downloads 1643205 Energy Efficient Assessment of Energy Internet Based on Data-Driven Fuzzy Integrated Cloud Evaluation Algorithm
Authors: Chuanbo Xu, Xinying Li, Gejirifu De, Yunna Wu
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Energy Internet (EI) is a new form that deeply integrates the Internet and the entire energy process from production to consumption. The assessment of energy efficient performance is of vital importance for the long-term sustainable development of EI project. Although the newly proposed fuzzy integrated cloud evaluation algorithm considers the randomness of uncertainty, it relies too much on the experience and knowledge of experts. Fortunately, the enrichment of EI data has enabled the utilization of data-driven methods. Therefore, the main purpose of this work is to assess the energy efficient of park-level EI by using a combination of a data-driven method with the fuzzy integrated cloud evaluation algorithm. Firstly, the indicators for the energy efficient are identified through literature review. Secondly, the artificial neural network (ANN)-based data-driven method is employed to cluster the values of indicators. Thirdly, the energy efficient of EI project is calculated through the fuzzy integrated cloud evaluation algorithm. Finally, the applicability of the proposed method is demonstrated by a case study.Keywords: energy efficient, energy internet, data-driven, fuzzy integrated evaluation, cloud model
Procedia PDF Downloads 1953204 Development of a General Purpose Computer Programme Based on Differential Evolution Algorithm: An Application towards Predicting Elastic Properties of Pavement
Authors: Sai Sankalp Vemavarapu
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This paper discusses the application of machine learning in the field of transportation engineering for predicting engineering properties of pavement more accurately and efficiently. Predicting the elastic properties aid us in assessing the current road conditions and taking appropriate measures to avoid any inconvenience to commuters. This improves the longevity and sustainability of the pavement layer while reducing its overall life-cycle cost. As an example, we have implemented differential evolution (DE) in the back-calculation of the elastic modulus of multi-layered pavement. The proposed DE global optimization back-calculation approach is integrated with a forward response model. This approach treats back-calculation as a global optimization problem where the cost function to be minimized is defined as the root mean square error in measured and computed deflections. The optimal solution which is elastic modulus, in this case, is searched for in the solution space by the DE algorithm. The best DE parameter combinations and the most optimum value is predicted so that the results are reproducible whenever the need arises. The algorithm’s performance in varied scenarios was analyzed by changing the input parameters. The prediction was well within the permissible error, establishing the supremacy of DE.Keywords: cost function, differential evolution, falling weight deflectometer, genetic algorithm, global optimization, metaheuristic algorithm, multilayered pavement, pavement condition assessment, pavement layer moduli back calculation
Procedia PDF Downloads 1583203 Image Rotation Using an Augmented 2-Step Shear Transform
Authors: Hee-Choul Kwon, Heeyong Kwon
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Image rotation is one of main pre-processing steps for image processing or image pattern recognition. It is implemented with a rotation matrix multiplication. It requires a lot of floating point arithmetic operations and trigonometric calculations, so it takes a long time to execute. Therefore, there has been a need for a high speed image rotation algorithm without two major time-consuming operations. However, the rotated image has a drawback, i.e. distortions. We solved the problem using an augmented two-step shear transform. We compare the presented algorithm with the conventional rotation with images of various sizes. Experimental results show that the presented algorithm is superior to the conventional rotation one.Keywords: high-speed rotation operation, image rotation, transform matrix, image processing, pattern recognition
Procedia PDF Downloads 2713202 Proximal Method of Solving Split System of Minimization Problem
Authors: Anteneh Getachew Gebrie, Rabian Wangkeeree
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The purpose of this paper is to introduce iterative algorithm solving split system of minimization problem given as a task of finding a common minimizer point of finite family of proper, lower semicontinuous convex functions and whose image under a bounded linear operator is also common minimizer point of another finite family of proper, lower semicontinuous convex functions. We obtain strong convergence of the sequence generated by our algorithm under some suitable conditions on the parameters. The iterative schemes are developed with a way of selecting the step sizes such that the information of operator norm is not necessary. Some applications and numerical experiment is given to analyse the efficiency of our algorithm.Keywords: Hilbert Space, minimization problems, Moreau-Yosida approximate, split feasibility problem
Procedia PDF Downloads 1353201 Engineering Optimization Using Two-Stage Differential Evolution
Authors: K. Y. Tseng, C. Y. Wu
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This paper employs a heuristic algorithm to solve engineering problems including truss structure optimization and optimal chiller loading (OCL) problems. Two different type algorithms, real-valued differential evolution (DE) and modified binary differential evolution (MBDE), are successfully integrated and then can obtain better performance in solving engineering problems. In order to demonstrate the performance of the proposed algorithm, this study adopts each one testing case of truss structure optimization and OCL problems to compare the results of other heuristic optimization methods. The result indicates that the proposed algorithm can obtain similar or better solution in comparing with previous studies.Keywords: differential evolution, Truss structure optimization, optimal chiller loading, modified binary differential evolution
Procedia PDF Downloads 1613200 Two Points Crossover Genetic Algorithm for Loop Layout Design Problem
Authors: Xu LiYun, Briand Florent, Fan GuoLiang
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The loop-layout design problem (LLDP) aims at optimizing the sequence of positioning of the machines around the cyclic production line. Traffic congestion is the usual criteria to minimize in this type of problem, i.e. the number of additional cycles spent by each part in the network until the completion of its required routing sequence of machines. This paper aims at applying several improvements mechanisms such as a positioned-based crossover operator for the Genetic Algorithm (GA) called a Two Points Crossover (TPC) and an offspring selection process. The performance of the improved GA is measured using well-known examples from literature and compared to other evolutionary algorithms. Good results show that GA can still be competitive for this type of problem against more recent evolutionary algorithms.Keywords: crossover, genetic algorithm, layout design problem, loop-layout, manufacturing optimization
Procedia PDF Downloads 2703199 Digital Control Algorithm Based on Delta-Operator for High-Frequency DC-DC Switching Converters
Authors: Renkai Wang, Tingcun Wei
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In this paper, a digital control algorithm based on delta-operator is presented for high-frequency digitally-controlled DC-DC switching converters. The stability and the controlling accuracy of the DC-DC switching converters are improved by using the digital control algorithm based on delta-operator without increasing the hardware circuit scale. The design method of voltage compensator in delta-domain using PID (Proportion-Integration- Differentiation) control is given in this paper, and the simulation results based on Simulink platform are provided, which have verified the theoretical analysis results very well. It can be concluded that, the presented control algorithm based on delta-operator has better stability and controlling accuracy, and easier hardware implementation than the existed control algorithms based on z-operator, therefore it can be used for the voltage compensator design in high-frequency digitally- controlled DC-DC switching converters.Keywords: digitally-controlled DC-DC switching converter, digital voltage compensator, delta-operator, finite word length, stability
Procedia PDF Downloads 4043198 Application of Fourier Series Based Learning Control on Mechatronic Systems
Authors: Sandra Baßler, Peter Dünow, Mathias Marquardt
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A Fourier series based learning control (FSBLC) algorithm for tracking trajectories of mechanical systems with unknown nonlinearities is presented. Two processes are introduced to which the FSBLC with PD controller is applied. One is a simplified service robot capable of climbing stairs due to special wheels and the other is a propeller driven pendulum with nearly the same requirements on control. Additionally to the investigation of learning the feed forward for the desired trajectories some considerations on the implementation of such an algorithm on low cost microcontroller hardware are made. Simulations of the service robot as well as practical experiments on the pendulum show the capability of the used FSBLC algorithm to perform the task of improving control behavior for repetitive task of such mechanical systems.Keywords: climbing stairs, FSBLC, ILC, service robot
Procedia PDF Downloads 3063197 Finding Data Envelopment Analysis Target Using the Multiple Objective Linear Programming Structure in Full Fuzzy Case
Authors: Raziyeh Shamsi
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In this paper, we present a multiple objective linear programming (MOLP) problem in full fuzzy case and find Data Envelopment Analysis(DEA) targets. In the presented model, we are seeking the least inputs and the most outputs in the production possibility set (PPS) with the variable return to scale (VRS) assumption, so that the efficiency projection is obtained for all decision making units (DMUs). Then, we provide an algorithm for finding DEA targets interactively in the full fuzzy case, which solves the full fuzzy problem without defuzzification. Owing to the use of interactive methods, the targets obtained by our algorithm are more applicable, more realistic, and they are according to the wish of the decision maker. Finally, an application of the algorithm in 21 educational institutions is provided.Keywords: DEA, MOLP, full fuzzy, target
Procedia PDF Downloads 2993196 Enhanced Weighted Centroid Localization Algorithm for Indoor Environments
Authors: I. Nižetić Kosović, T. Jagušt
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Lately, with the increasing number of location-based applications, demand for highly accurate and reliable indoor localization became urgent. This is a challenging problem, due to the measurement variance which is the consequence of various factors like obstacles, equipment properties and environmental changes in complex nature of indoor environments. In this paper we propose low-cost custom-setup infrastructure solution and localization algorithm based on the Weighted Centroid Localization (WCL) method. Localization accuracy is increased by several enhancements: calibration of RSSI values gained from wireless nodes, repetitive measurements of RSSI to exclude deviating values from the position estimation, and by considering orientation of the device according to the wireless nodes. We conducted several experiments to evaluate the proposed algorithm. High accuracy of ~1m was achieved.Keywords: indoor environment, received signal strength indicator, weighted centroid localization, wireless localization
Procedia PDF Downloads 2273195 A New Method to Winner Determination for Economic Resource Allocation in Cloud Computing Systems
Authors: Ebrahim Behrouzian Nejad, Rezvan Alipoor Sabzevari
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Cloud computing systems are large-scale distributed systems, so that they focus more on large scale resource sharing, cooperation of several organizations and their use in new applications. One of the main challenges in this realm is resource allocation. There are many different ways to resource allocation in cloud computing. One of the common methods to resource allocation are economic methods. Among these methods, the auction-based method has greater prominence compared with Fixed-Price method. The double combinatorial auction is one of the proper ways of resource allocation in cloud computing. This method includes two phases: winner determination and resource allocation. In this paper a new method has been presented to determine winner in double combinatorial auction-based resource allocation using Imperialist Competitive Algorithm (ICA). The experimental results show that in our new proposed the number of winner users is higher than genetic algorithm. On other hand, in proposed algorithm, the number of winner providers is higher in genetic algorithm.Keywords: cloud computing, resource allocation, double auction, winner determination
Procedia PDF Downloads 3543194 Anisotropic Total Fractional Order Variation Model in Seismic Data Denoising
Authors: Jianwei Ma, Diriba Gemechu
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In seismic data processing, attenuation of random noise is the basic step to improve quality of data for further application of seismic data in exploration and development in different gas and oil industries. The signal-to-noise ratio of the data also highly determines quality of seismic data. This factor affects the reliability as well as the accuracy of seismic signal during interpretation for different purposes in different companies. To use seismic data for further application and interpretation, we need to improve the signal-to-noise ration while attenuating random noise effectively. To improve the signal-to-noise ration and attenuating seismic random noise by preserving important features and information about seismic signals, we introduce the concept of anisotropic total fractional order denoising algorithm. The anisotropic total fractional order variation model defined in fractional order bounded variation is proposed as a regularization in seismic denoising. The split Bregman algorithm is employed to solve the minimization problem of the anisotropic total fractional order variation model and the corresponding denoising algorithm for the proposed method is derived. We test the effectiveness of theproposed method for synthetic and real seismic data sets and the denoised result is compared with F-X deconvolution and non-local means denoising algorithm.Keywords: anisotropic total fractional order variation, fractional order bounded variation, seismic random noise attenuation, split Bregman algorithm
Procedia PDF Downloads 2033193 Evaluation of Water Management Options to Improve the Crop Yield and Water Productivity for Semi-Arid Watershed in Southern India Using AquaCrop Model
Authors: V. S. Manivasagam, R. Nagarajan
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Modeling the soil, water and crop growth interactions are attaining major importance, considering the future climate change and water availability for agriculture to meet the growing food demand. Progress in understanding the crop growth response during water stress period through crop modeling approach provides an opportunity for improving and sustaining the future agriculture water use efficiency. An attempt has been made to evaluate the potential use of crop modeling approach for assessing the minimal supplementary irrigation requirement for crop growth during water limited condition and its practical significance in sustainable improvement of crop yield and water productivity. Among the numerous crop models, water driven-AquaCrop model has been chosen for the present study considering the modeling approach and water stress impact on yield simulation. The study has been evaluated in rainfed maize grown area of semi-arid Shanmuganadi watershed (a tributary of the Cauvery river system) located in southern India during the rabi cropping season (October-February). In addition to actual rainfed maize growth simulation, irrigated maize scenarios were simulated for assessing the supplementary irrigation requirement during water shortage condition for the period 2012-2015. The simulation results for rainfed maize have shown that the average maize yield of 0.5-2 t ha-1 was observed during deficit monsoon season (<350 mm) whereas 5.3 t ha-1 was noticed during sufficient monsoonal period (>350 mm). Scenario results for irrigated maize simulation during deficit monsoonal period has revealed that 150-200 mm of supplementary irrigation has ensured the 5.8 t ha-1 of irrigated maize yield. Thus, study results clearly portrayed that minimal application of supplementary irrigation during the critical growth period along with the deficit rainfall has increased the crop water productivity from 1.07 to 2.59 kg m-3 for major soil types. Overall, AquaCrop is found to be very effective for the sustainable irrigation assessment considering the model simplicity and minimal inputs requirement.Keywords: AquaCrop, crop modeling, rainfed maize, water stress
Procedia PDF Downloads 2603192 Solving the Wireless Mesh Network Design Problem Using Genetic Algorithm and Simulated Annealing Optimization Methods
Authors: Moheb R. Girgis, Tarek M. Mahmoud, Bahgat A. Abdullatif, Ahmed M. Rabie
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Mesh clients, mesh routers and gateways are components of Wireless Mesh Network (WMN). In WMN, gateways connect to Internet using wireline links and supply Internet access services for users. We usually need multiple gateways, which takes time and costs a lot of money set up, due to the limited wireless channel bit rate. WMN is a highly developed technology that offers to end users a wireless broadband access. It offers a high degree of flexibility contrasted to conventional networks; however, this attribute comes at the expense of a more complex construction. Therefore, a challenge is the planning and optimization of WMNs. In this paper, we concentrate on this challenge using a genetic algorithm and simulated annealing. The genetic algorithm and simulated annealing enable searching for a low-cost WMN configuration with constraints and determine the number of used gateways. Experimental results proved that the performance of the genetic algorithm and simulated annealing in minimizing WMN network costs while satisfying quality of service. The proposed models are presented to significantly outperform the existing solutions.Keywords: wireless mesh networks, genetic algorithms, simulated annealing, topology design
Procedia PDF Downloads 4523191 Applying Genetic Algorithm in Exchange Rate Models Determination
Authors: Mehdi Rostamzadeh
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Genetic Algorithms (GAs) are an adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetic. In this study, we apply GAs for fundamental and technical models of exchange rate determination in exchange rate market. In this framework, we estimated absolute and relative purchasing power parity, Mundell-Fleming, sticky and flexible prices (monetary models), equilibrium exchange rate and portfolio balance model as fundamental models and Auto Regressive (AR), Moving Average (MA), Auto-Regressive with Moving Average (ARMA) and Mean Reversion (MR) as technical models for Iranian Rial against European Union’s Euro using monthly data from January 1992 to December 2014. Then, we put these models into the genetic algorithm system for measuring their optimal weight for each model. These optimal weights have been measured according to four criteria i.e. R-Squared (R2), mean square error (MSE), mean absolute percentage error (MAPE) and root mean square error (RMSE).Based on obtained Results, it seems that for explaining of Iranian Rial against EU Euro exchange rate behavior, fundamental models are better than technical models.Keywords: exchange rate, genetic algorithm, fundamental models, technical models
Procedia PDF Downloads 2673190 Signal Processing of the Blood Pressure and Characterization
Authors: Hadj Abd El Kader Benghenia, Fethi Bereksi Reguig
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In clinical medicine, blood pressure, raised blood hemodynamic monitoring is rich pathophysiological information of cardiovascular system, of course described through factors such as: blood volume, arterial compliance and peripheral resistance. In this work, we are interested in analyzing these signals to propose a detection algorithm to delineate the different sequences and especially systolic blood pressure (SBP), diastolic blood pressure (DBP), and the wave and dicrotic to do their analysis in order to extract the cardiovascular parameters.Keywords: blood pressure, SBP, DBP, detection algorithm
Procedia PDF Downloads 4283189 Optimal Emergency Shipment Policy for a Single-Echelon Periodic Review Inventory System
Authors: Saeed Poormoaied, Zumbul Atan
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Emergency shipments provide a powerful mechanism to alleviate the risk of imminent stock-outs and can result in substantial benefits in an inventory system. Customer satisfaction and high service level are immediate consequences of utilizing emergency shipments. In this paper, we consider a single-echelon periodic review inventory system consisting of a single local warehouse, being replenished from a central warehouse with ample capacity in an infinite horizon setting. Since the structure of the optimal policy appears to be complicated, we analyze this problem under an order-up-to-S inventory control policy framework, the (S, T) policy, with the emergency shipment consideration. In each period of the periodic review policy, there is a single opportunity at any point of time for the emergency shipment so that in case of stock-outs, an emergency shipment is requested. The goal is to determine the timing and amount of the emergency shipment during a period (emergency shipment policy) as well as the base stock periodic review policy parameters (replenishment policy). We show that how taking advantage of having an emergency shipment during periods improves the performance of the classical (S, T) policy, especially when fixed and unit emergency shipment costs are small. Investigating the structure of the objective function, we develop an exact algorithm for finding the optimal solution. We also provide a heuristic and an approximation algorithm for the periodic review inventory system problem. The experimental analyses indicate that the heuristic algorithm is computationally more efficient than the approximation algorithm, but in terms of the solution efficiency, the approximation algorithm performs very well. We achieve up to 13% cost savings in the (S, T) policy if we apply the proposed emergency shipment policy. Moreover, our computational results reveal that the approximated solution is often within 0.21% of the globally optimal solution.Keywords: emergency shipment, inventory, periodic review policy, approximation algorithm.
Procedia PDF Downloads 1343188 New Two-Way Map-Reduce Join Algorithm: Hash Semi Join
Authors: Marwa Hussein Mohamed, Mohamed Helmy Khafagy, Samah Ahmed Senbel
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Map Reduce is a programming model used to handle and support massive data sets. Rapidly increasing in data size and big data are the most important issue today to make an analysis of this data. map reduce is used to analyze data and get more helpful information by using two simple functions map and reduce it's only written by the programmer, and it includes load balancing , fault tolerance and high scalability. The most important operation in data analysis are join, but map reduce is not directly support join. This paper explains two-way map-reduce join algorithm, semi-join and per split semi-join, and proposes new algorithm hash semi-join that used hash table to increase performance by eliminating unused records as early as possible and apply join using hash table rather than using map function to match join key with other data table in the second phase but using hash tables isn't affecting on memory size because we only save matched records from the second table only. Our experimental result shows that using a hash table with hash semi-join algorithm has higher performance than two other algorithms while increasing the data size from 10 million records to 500 million and running time are increased according to the size of joined records between two tables.Keywords: map reduce, hadoop, semi join, two way join
Procedia PDF Downloads 5083187 Solving Flowshop Scheduling Problems with Ant Colony Optimization Heuristic
Authors: Arshad Mehmood Ch, Riaz Ahmad, Imran Ali Ch, Waqas Durrani
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This study deals with the application of Ant Colony Optimization (ACO) approach to solve no-wait flowshop scheduling problem (NW-FSSP). ACO algorithm so developed has been coded on Matlab computer application. The paper covers detailed steps to apply ACO and focuses on judging the strength of ACO in relation to other solution techniques previously applied to solve no-wait flowshop problem. The general purpose approach was able to find reasonably accurate solutions for almost all the problems under consideration and was able to handle a fairly large spectrum of problems with far reduced CPU effort. Careful scrutiny of the results reveals that the algorithm presented results better than other approaches like Genetic algorithm and Tabu Search heuristics etc; earlier applied to solve NW-FSSP data sets.Keywords: no-wait, flowshop, scheduling, ant colony optimization (ACO), makespan
Procedia PDF Downloads 4273186 Taguchi Method for Analyzing a Flexible Integrated Logistics Network
Authors: E. Behmanesh, J. Pannek
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Logistics network design is known as one of the strategic decision problems. As these kinds of problems belong to the category of NP-hard problems, traditional ways are failed to find an optimal solution in short time. In this study, we attempt to involve reverse flow through an integrated design of forward/reverse supply chain network that formulated into a mixed integer linear programming. This Integrated, multi-stages model is enriched by three different delivery path which makes the problem more complex. To tackle with such an NP-hard problem a revised random path direct encoding method based memetic algorithm is considered as the solution methodology. Each algorithm has some parameters that need to be investigate to reveal the best performance. In this regard, Taguchi method is adapted to identify the optimum operating condition of the proposed memetic algorithm to improve the results. In this study, four factors namely, population size, crossover rate, local search iteration and a number of iteration are considered. Analyzing the parameters and improvement in results are the outlook of this research.Keywords: integrated logistics network, flexible path, memetic algorithm, Taguchi method
Procedia PDF Downloads 1843185 Soil Properties and Crop Productivity of Kiln Sites in the Highlands of North-western Ethiopia
Authors: Hanamariam Mekonnen
Abstract:
Ethiopian farmers traditionally produce charcoal under several kilns on cultivated land: particularly in Kasiry micro-watershed Fagita Lekoma district of Northwestern Ethiopia. However, the effects of such soil heating and remnants of charcoal leftover on soils have not been adequately documented. Hence, this study tried to quantify the effects of such kiln sites on selected soil properties and wheat crop performance. Soils from four kiln sites were thus purposively sampled at depths of 0-20 cm, 20-40 cm and 40-60 cm and were compared with the respective soil layers of none-kiln sites from similar adjacent fields. While soil moisture content was sampled at kiln and none-kiln site in wet and dry seasons from each depth. In addition, a pot experiment was conducted using two sources of biochar (Acacia decurrens and Eucalyptus Camaldulensis) with four rates (0, 10, 20, and 40 t/ha) and compared with crops grown from soils of 1kiln sites without biochar application laid out in a CRD with three replications. The data were analyzed using SAS software Version 9.4.The result revealed notable variations of kiln site soils and along soil depth. The appreciable increased (p<0.05) soil pH (5.5 to 5.74), organic carbon (3.89 to 4.27%), TN (0.30 to 0.32%), CEC (32.59 to 35.23 cmolckg-1), Ca (6.44 to 7.9 cmolckg-1), Mg (4.48 to 5.46 cmolckg-1), and significantly (p<0.01) Av. P (30.25 to 46.4 ppm) and K (2.11 to 2.82 cmolckg-1) were recorded from the none-kiln to kiln soils, respectively. On the other hand, ex. acidity and aluminum, available Fe and Mn were reduced from 2.20 to 1.54, 1.95 to 1.31 cmolckg-1 and 57.46 to 41.40 and 5.65 to 3.86 ppm, respectively, from the control to the kiln. Soil texture was significantly affected by soil heating and along soil depth. The sand content was (p<0.05) varied between the value of 23% to 29% from none-kiln to kiln site, and clay content was (p<0.01) increased from 0-20 cm (32%) soil depth to 40-60 cm (43%) deeper soil. Significantly (p<0.05) higher Soil moisture content was recorded at none-kiln site (45.85%) compared to kiln (40.44%) in wet season, whereas in dry season, lower moisture content was revealed at kiln site (26%) compared to none-kiln (30.7%). As wet to dry season, soil moisture was decreased from 43% to 28% respectively. Bulk density (P<0.01) varied between 0.88 to 0.94 gcm-3 from control to kiln in dry season. Similarly, the value of soil pH (6.10), Av. P (58.12), exchangeable bases (Ca (9.83), Mg (6.19) and K (3.67)) were (p<0.01) higher at the 0-20 cm soil depth as compared to the deeper soils, the result of soil moisture (30 to 42%) and CEC (31 to 36 cmolckg-1) increased down the soil profile. After wheat harvest, soil pH, Av. P, CEC, and exchangeable bases (Mg, K and Na) were significantly higher in the kiln soil, while soil moisture and OC increased by the applied biochar of 20 and 40 ton/ha. High yield 2.28 gpot-1 (p<0.01) was recorded in kiln soil, growth parameters of wheat were significantly increased with increasing biochar rates.Keywords: biochar, kasiry micro-watershed, kiln site, none-kiln site, soil properties
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