Search results for: variable neighborhood search

Authors: Se Kyung Oh, Young Hwan Yoon, Ary Bachtiar Krishna

Abstract:

Nowadays, a passenger car suspension must has high performance criteria with light weight, low cost, and low energy consumption. Pilot controlled proportional valve is designed and analyzed to get small pressure change rate after blow-off, and to get a fast response of the damper, a reverse damping mechanism is adapted. The reverse continuous variable damper is designed as a HS-SH damper which offers good body control with reduced transferred input force from the tire, compared with any other type of suspension system. The damper structure is designed, so that rebound and compression damping forces can be tuned independently, of which the variable valve is placed externally. The rate of pressure change with respect to the flow rate after blow-off becomes smooth when the fixed orifice size increases, which means that the blow-off slope is controllable using the fixed orifice size. Damping forces are measured with the change of the solenoid current at the different piston velocities to confirm the maximum hysteresis of 20 N, linearity, and variance of damping force. The damping force variance is wide and continuous, and is controlled by the spool opening, of which scheme is usually adapted in proportional valves. The reverse continuous variable damper developed in this study is expected to be utilized in the semi-active suspension systems in passenger cars after its performance and simplicity of the design is confirmed through a real car test.

Keywords: Blow-off, damping force, pilot controlledproportional valve, reverse continuous damper.

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Authors: Vijaya K. Srivastava, Davide Spinello

Abstract:

This paper presents performance of two robust gradient-based heuristic optimization procedures based on 3ⁿ enumeration and tunneling approach to seek global optimum of constrained integer problems. Both these procedures consist of two distinct phases for locating the global optimum of integer problems with a linear or non-linear objective function subject to linear or non-linear constraints. In both procedures, in the first phase, a local minimum of the function is found using the gradient approach coupled with hemstitching moves when a constraint is violated in order to return the search to the feasible region. In the second phase, in one optimization procedure, the second sub-procedure examines 3ⁿ integer combinations on the boundary and within hypercube volume encompassing the result neighboring the result from the first phase and in the second optimization procedure a tunneling function is constructed at the local minimum of the first phase so as to find another point on the other side of the barrier where the function value is approximately the same. In the next cycle, the search for the global optimum commences in both optimization procedures again using this new-found point as the starting vector. The search continues and repeated for various step sizes along the function gradient as well as that along the vector normal to the violated constraints until no improvement in optimum value is found. The results from both these proposed optimization methods are presented and compared with one provided by popular MS Excel solver that is provided within MS Office suite and other published results.

Keywords: Constrained integer problems, enumerative search algorithm, Heuristic algorithm, tunneling algorithm.

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Authors: Ahmad Tariq Sheikh, Shahzad Amin Sheikh

Abstract:

A new distance-adjusted approach is proposed in which static square contours are defined around an estimated symbol in a QAM constellation, which create regions that correspond to fixed step sizes and weighting factors. As a result, the equalizer tap adjustment consists of a linearly weighted sum of adaptation criteria that is scaled by a variable step size. This approach is the basis of two new algorithms: the Variable step size Square Contour Algorithm (VSCA) and the Variable step size Square Contour Decision-Directed Algorithm (VSDA). The proposed schemes are compared with existing blind equalization algorithms in the SCA family in terms of convergence speed, constellation eye opening and residual ISI suppression. Simulation results for 64-QAM signaling over empirically derived microwave radio channels confirm the efficacy of the proposed algorithms. An RTL implementation of the blind adaptive equalizer based on the proposed schemes is presented and the system is configured to operate in VSCA error signal mode, for square QAM signals up to 64-QAM.

Keywords: Adaptive filtering, Blind Equalization, Square Contour Algorithm.

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Authors: Avishai Sintov, Roland Menassa, Amir Shapiro

Abstract:

Industrial robotic arms utilize multiple end-effectors, each for a specific part and for a specific task. We propose a novel algorithm which will define a single end-effector’s configuration able to grasp a given set of objects with different geometries. The algorithm will have great benefit in production lines allowing a single robot to grasp various parts. Hence, reducing the number of endeffectors needed. Moreover, the algorithm will reduce end-effector design and manufacturing time and final product cost. The algorithm searches for a common grasp over the set of objects. The search algorithm maps all possible grasps for each object which satisfy a quality criterion and takes into account possible external wrenches (forces and torques) applied to the object. The mapped grasps are- represented by high-dimensional feature vectors which describes the shape of the gripper. We generate a database of all possible grasps for each object in the feature space. Then we use a search and classification algorithm for intersecting all possible grasps over all parts and finding a single common grasp suitable for all objects. We present simulations of planar and spatial objects to validate the feasibility of the approach.

Keywords: Common Grasping, Search Algorithm, Robotic End-Effector.

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Authors: Timothy E. Frank, Josh R. Aldred, Sophie B. Boulware, Michelle K. Cabonce, Justin H. White

Abstract:

Materials degrade at different rates in different environments depending on factors such as temperature, aridity, salinity, and solar radiation. Therefore, predicting asset longevity depends, in part, on the environmental conditions to which the asset is exposed. Heating, ventilation, and air conditioning (HVAC) systems are critical to building operations yet are responsible for a significant proportion of their energy consumption. HVAC energy use increases substantially with slight operational inefficiencies. Understanding the environmental influences on HVAC degradation in detail will inform maintenance schedules and capital investment, reduce energy use, and increase lifecycle management efficiency. HVAC inspection records spanning 14 years from 21 locations across the United States were compiled and associated with the climate conditions to which they were exposed. Three environmental features were explored in this study: average high temperature, average low temperature, and annual precipitation, as well as four non-environmental features. Initial insights showed no correlations between individual features and the rate of HVAC component degradation. Using neighborhood component analysis, however, the most critical features related to degradation were identified. Two models were considered, and results varied between them. However, longitude and latitude emerged as potentially the best predictors of average HVAC component degradation. Further research is needed to evaluate additional environmental features, increase the resolution of the environmental data, and develop more robust models to achieve more conclusive results.

Keywords: Climate, infrastructure degradation, HVAC, neighborhood component analysis.

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Authors: H. Arabi, A.R. Kamali Asl

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The purpose of this work is measurement of the system presampling MTF of a variable resolution x-ray (VRX) CT scanner. In this paper, we used the parameters of an actual VRX CT scanner for simulation and study of effect of different focal spot sizes on system presampling MTF by Monte Carlo method (GATE simulation software). Focal spot size of 0.6 mm limited the spatial resolution of the system to 5.5 cy/mm at incident angles of below 17º for cell#1. By focal spot size of 0.3 mm the spatial resolution increased up to 11 cy/mm and the limiting effect of focal spot size appeared at incident angles of below 9º. The focal spot size of 0.3 mm could improve the spatial resolution to some extent but because of magnification non-uniformity, there is a 10 cy/mm difference between spatial resolution of cell#1 and cell#256. The focal spot size of 0.1 mm acted as an ideal point source for this system. The spatial resolution increased to more than 35 cy/mm and at all incident angles the spatial resolution was a function of incident angle. By the way focal spot size of 0.1 mm minimized the effect of magnification nonuniformity.

Keywords: Focal spot, Spatial resolution, Monte Carlosimulation, Variable resolution x-ray (VRX) CT.

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Authors: Shimal Das, Dibyendu Ghoshal

Abstract:

The effect of directional search using iterated functional system has been studied on four images taken from databases. The images are portioned successively towards smaller dimension. Presented method provides the faster rate of convergence with respect to processing time in the flat region, but the same has been found to be slower at the border of the images and edges. It has also been revealed that the PSNR is lower at the edges and border portions of the image, and it is found to be higher in the uniform gray region, under the same external illumination and external noise environment.

Keywords: Iterated functional system, fractal compression, structural similarity index measure, fractal block coding, affine transformations.

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Authors: Nuanpan Nangsue

Abstract:

Ratio and regression type estimators have been used by previous authors to estimate a population mean for the principal variable from samples in which both auxiliary x and principal y variable data are available. However, missing data are a common problem in statistical analyses with real data. Ratio and regression type estimators have also been used for imputing values of missing y data. In this paper, six new ratio and regression type estimators are proposed for imputing values for any missing y data and estimating a population mean for y from samples with missing x and/or y data. A simulation study has been conducted to compare the six ratio and regression type estimators with a previous estimator of Rueda. Two population sizes N = 1,000 and 5,000 have been considered with sample sizes of 10% and 30% and with correlation coefficients between population variables X and Y of 0.5 and 0.8. In the simulations, 10 and 40 percent of sample y values and 10 and 40 percent of sample x values were randomly designated as missing. The new ratio and regression type estimators give similar mean absolute percentage errors that are smaller than the Rueda estimator for all cases. The new estimators give a large reduction in errors for the case of 40% missing y values and sampling fraction of 30%.

Keywords: Auxiliary variable, missing data, ratio and regression type estimators.

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Authors: Awais Adnan, Muhammad Ali, Amir Hanif Dar

Abstract:

Image Searching was always a problem specially when these images are not properly managed or these are distributed over different locations. Currently different techniques are used for image search. On one end, more features of the image are captured and stored to get better results. Storing and management of such features is itself a time consuming job. While on the other extreme if fewer features are stored the accuracy rate is not satisfactory. Same image stored with different visual properties can further reduce the rate of accuracy. In this paper we present a new concept of using polynomials of sorted histogram of the image. This approach need less overhead and can cope with the difference in visual features of image.

Keywords: Sorted Histogram, Polynomial Curves, feature pointsof images, Grayscale, visual properties of image.

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Authors: M. Saravi, F. Ashrafi, S.R. Mirrajei

Abstract:

As we know, most differential equations concerning physical phenomenon could not be solved by analytical method. Even if we use Series Method, some times we need an appropriate change of variable, and even when we can, their closed form solution may be so complicated that using it to obtain an image or to examine the structure of the system is impossible. For example, if we consider Schrodinger equation, i.e., We come to a three-term recursion relations, which work with it takes, at least, a little bit time to get a series solution[6]. For this reason we use a change of variable such as or when we consider the orbital angular momentum[1], it will be necessary to solve. As we can observe, working with this equation is tedious. In this paper, after introducing Clenshaw method, which is a kind of Spectral method, we try to solve some of such equations.

Keywords: Chebyshev polynomials, Clenshaw method, ODEs, Spectral methods

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Authors: Maciej Norberciak

Abstract:

Timetabling problems are often hard and timeconsuming to solve. Most of the methods of solving them concern only one problem instance or class. This paper describes a universal method for solving large, highly constrained timetabling problems from different domains. The solution is based on evolutionary algorithm-s framework and operates on two levels – first-level evolutionary algorithm tries to find a solution basing on given set of operating parameters, second-level algorithm is used to establish those parameters. Tabu search is employed to speed up the solution finding process on first level. The method has been used to solve three different timetabling problems with promising results.

Keywords: Evolutionary algorithms, tabu search, timetabling.

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Authors: Rajender Singh Chillar, Barjesh Kochar

Abstract:

All Text processing systems allow their users to search a pattern of string from a given text. String matching is fundamental to database and text processing applications. Every text editor must contain a mechanism to search the current document for arbitrary strings. Spelling checkers scan an input text for words in the dictionary and reject any strings that do not match. We store our information in data bases so that later on we can retrieve the same and this retrieval can be done by using various string matching algorithms. This paper is describing a new string matching algorithm for various applications. A new algorithm has been designed with the help of Rabin Karp Matcher, to improve string matching process.

Keywords: Algorithm, Complexity, Matching-patterns, Pattern, Rabin-Karp, String, text-processing.

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Authors: Sizhong Zhou

Abstract:

Let a and b be nonnegative integers with 2 ≤ a < b, and let G be a Hamiltonian graph of order n with n ≥ (a+b−4)(a+b−2) b−2 . An [a, b]-factor F of G is called a Hamiltonian [a, b]-factor if F contains a Hamiltonian cycle. In this paper, it is proved that G has a Hamiltonian [a, b]-factor if |NG(X)| > (a−1)n+|X|−1 a+b−3 for every nonempty independent subset X of V (G) and δ(G) > (a−1)n+a+b−4 a+b−3 .

Keywords: graph, minimum degree, neighborhood, [a, b]-factor, Hamiltonian [a, b]-factor.

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Authors: M. Nirmala

Abstract:

Power quality in terms of power factor, THD and precisely regulated output voltage are the major key factors for efficient operation of power electronic converters. This paper presents an easy and effective active wave shaping control scheme for the pulsed input current drawn by the uncontrolled diode bridge rectifier thereby achieving power factor nearer to unity and also satisfying the THD specifications. It also regulates the output DC-bus voltage. CCM boost power factor correction with constant frequency operation features smaller inductor current ripple resulting in low RMS currents on inductor and switch thus leading to low electromagnetic interference. The objective of this work is to develop an active PFC control circuit using CCM boost converter implementing variable duty cycle control. The proposed scheme eliminates inductor current sensing requirements yet offering good performance and satisfactory results for maintaining the power quality. Simulation results have been presented which covers load changes also.

Keywords: CCM Boost converter, Power factor Correction, Total harmonic distortion, Variable Duty Cycle.

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Authors: Truong Quang Dang Khoa, Masahiro Nakagawa

Abstract:

Chaos and fractals are novel fields of physics and mathematics showing up a new way of universe viewpoint and creating many ideas to solve several present problems. In this paper, a novel algorithm based on the chaotic sequence generator with the highest ability to adapt and reach the global optima is proposed. The adaptive ability of proposal algorithm is flexible in 2 steps. The first one is a breadth-first search and the second one is a depth-first search. The proposal algorithm is examined by 2 functions, the Camel function and the Schaffer function. Furthermore, the proposal algorithm is applied to optimize training Multilayer Neural Networks.

Keywords: learning and evolutionary computing, Chaos Optimization Algorithm, Artificial Neural Networks, nonlinear optimization, intelligent computational technologies.

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Authors: Hyung Suk Kang

Abstract:

A triangular fin with variable fin base thickness is analyzed and optimized using a two-dimensional analytical method. The influence of fin base height and fin base thickness on the temperature in the fin is listed. For the fixed fin volumes, the maximum heat loss, the corresponding optimum fin effectiveness, fin base height and fin tip length as a function of the fin base thickness, convection characteristic number and dimensionless fin volume are represented. One of the results shows that the optimum heat loss increases whereas the corresponding optimum fin effectiveness decreases with the increase of fin volume.

Keywords: A triangular fin, Convection characteristic number, Heat loss, Fin base thickness.

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Authors: Kanate Pantusavase, Jaramporn Hassamontr

Abstract:

This research aims to develop an algorithm to generate a schedule of multiple cranes that will maximize load throughputs in anodizing operation. The algorithm proposed utilizes an enumerative strategy to search for constant time between successive loads and crane covering range over baths. The computer program developed is able to generate a near-optimal crane schedule within reasonable times, i.e. within 10 minutes. Its results are compared with existing solutions from an aluminum extrusion industry. The program can be used to generate crane schedules for mixed products, thus allowing mixed-model line balancing to improve overall cycle times.

Keywords: Crane scheduling, anodizing operations, cycle time minimization.

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Authors: Hossein Abbasi

Abstract:

The stability is an important topic to plan and manage the energy in the microgrids as the same as the conventional power systems. The voltage and frequency stability is one of the most important issues recently studied in microgrids. The objectives of this paper are the modelling and designing of the components and optimal controllers for the voltage and frequency control of the AC/DC hybrid microgrid under the different disturbances. Since the PI controllers have the advantages of simple structure and easy implementation, so they are designed and modeled in this paper. The harmony search (HS) algorithm is used to optimize the controllers’ parameters. According to the achieved results, the PI controllers have a good performance in voltage and frequency control of the microgrid.

Keywords: Frequency control, HS algorithm, microgrid, PI controller, voltage control.

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Authors: S. Pushkar, O. Verbitsky

Abstract:

Currently, green rating systems are mainly utilized for correctly sizing mechanical and electrical systems, which have short lifetime expectancies. In these systems, passive solar and bio-climatic architecture, which have long lifetime expectancies, are neglected. Urban rating systems consider buildings and services in addition to neighborhoods and public transportation as integral parts of the built environment. The main goal of this study was to develop a more consistent point allocation system for urban building standards by using six different lifetime shearing layers: Site, Structure, Skin, Services, Space, and Stuff, each reflecting distinct environmental damages. This shearing-layer concept was applied to internationally well-known rating systems: Leadership in Energy and Environmental Design (LEED) for Neighborhood Development, BRE Environmental Assessment Method (BREEAM) for Communities and Comprehensive Assessment System for Building Environmental Efficiency (CASBEE) for Urban Development. The results showed that LEED for Neighborhood Development and BREEAM for Communities focused on long-lifetime-expectancy building designs, whereas CASBEE for Urban Development gave equal importance to the Building and Service Layers. Moreover, although this rating system was applied using a building-scale assessment, “Urban Area + Buildings” focuses on a short-lifetime-expectancy system design, neglecting to improve the architectural design by considering bioclimatic and passive solar aspects.

Keywords: Green rating system, passive solar architecture, shearing-layer concept, urban community.

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Authors: M. Zarei, A. Roozegar, R. Kazemzadeh, J.M. Kauffmann

Abstract:

This paper describes an efficient and practical method for economic dispatch problem in one and two area electrical power systems with considering the constraint of the tie transmission line capacity constraint. Direct search method (DSM) is used with some equality and inequality constraints of the production units with any kind of fuel cost function. By this method, it is possible to use several inequality constraints without having difficulty for complex cost functions or in the case of unavailability of the cost function derivative. To minimize the number of total iterations in searching, process multi-level convergence is incorporated in the DSM. Enhanced direct search method (EDSM) for two area power system will be investigated. The initial calculation step size that causes less iterations and then less calculation time is presented. Effect of the transmission tie line capacity, between areas, on economic dispatch problem and on total generation cost will be studied; line compensation and active power with reactive power dispatch are proposed to overcome the high generation costs for this multi-area system.

Keywords: Economic dispatch, Power System Operation, Direct Search Method, Transmission Capacity Constraint.

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Authors: P. Luangpaiboon, S. Boonhao

Abstract:

This study proposes a multi-response surface optimization problem (MRSOP) for determining the proper choices of a process parameter design (PPD) decision problem in a noisy environment of a grease position process in an electronic industry. The proposed models attempts to maximize dual process responses on the mean of parts between failure on left and right processes. The conventional modified simplex method and its hybridization of the stochastic operator from the hunting search algorithm are applied to determine the proper levels of controllable design parameters affecting the quality performances. A numerical example demonstrates the feasibility of applying the proposed model to the PPD problem via two iterative methods. Its advantages are also discussed. Numerical results demonstrate that the hybridization is superior to the use of the conventional method. In this study, the mean of parts between failure on left and right lines improve by 39.51%, approximately. All experimental data presented in this research have been normalized to disguise actual performance measures as raw data are considered to be confidential.

Keywords: Grease Position Process, Multi-response Surfaces, Modified Simplex Method, Hunting Search Method, Desirability Function Approach.

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Authors: Satyanadh Gundimada, Vijayan K Asari

Abstract:

A novel feature selection strategy to improve the recognition accuracy on the faces that are affected due to nonuniform illumination, partial occlusions and varying expressions is proposed in this paper. This technique is applicable especially in scenarios where the possibility of obtaining a reliable intra-class probability distribution is minimal due to fewer numbers of training samples. Phase congruency features in an image are defined as the points where the Fourier components of that image are maximally inphase. These features are invariant to brightness and contrast of the image under consideration. This property allows to achieve the goal of lighting invariant face recognition. Phase congruency maps of the training samples are generated and a novel modular feature selection strategy is implemented. Smaller sub regions from a predefined neighborhood within the phase congruency images of the training samples are merged to obtain a large set of features. These features are arranged in the order of increasing distance between the sub regions involved in merging. The assumption behind the proposed implementation of the region merging and arrangement strategy is that, local dependencies among the pixels are more important than global dependencies. The obtained feature sets are then arranged in the decreasing order of discriminating capability using a criterion function, which is the ratio of the between class variance to the within class variance of the sample set, in the PCA domain. The results indicate high improvement in the classification performance compared to baseline algorithms.

Keywords: Discriminant analysis, intra-class probability distribution, principal component analysis, phase congruency.

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Authors: Salinee Thumronglaohapun

Abstract:

The proper number and appropriate locations of service centers can save cost, raise revenue and gain more satisfaction from customers. Establishing service centers is high-cost and difficult to relocate. In long-term planning periods, several factors may affect the service. One of the most critical factors is uncertain demand of customers. The opened service centers need to be capable of serving customers and making a profit although the demand in each period is changed. In this work, the capacitated location-allocation problem with stochastic demand is considered. A mathematical model is formulated to determine suitable locations of service centers and their allocation to maximize total profit for multiple planning periods. Two heuristic methods, a local search and genetic algorithm, are used to solve this problem. For the local search, five different chances to choose each type of moves are applied. For the genetic algorithm, three different replacement strategies are considered. The results of applying each method to solve numerical examples are compared. Both methods reach to the same best found solution in most examples but the genetic algorithm provides better solutions in some cases.

Keywords: Location-allocation problem, stochastic demand, local search, genetic algorithm.

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Authors: Razib M. Othman, Safaai Deris, Rosli M. Illias

Abstract:

Annotation of a protein sequence is pivotal for the understanding of its function. Accuracy of manual annotation provided by curators is still questionable by having lesser evidence strength and yet a hard task and time consuming. A number of computational methods including tools have been developed to tackle this challenging task. However, they require high-cost hardware, are difficult to be setup by the bioscientists, or depend on time intensive and blind sequence similarity search like Basic Local Alignment Search Tool. This paper introduces a new method of assigning highly correlated Gene Ontology terms of annotated protein sequences to partially annotated or newly discovered protein sequences. This method is fully based on Gene Ontology data and annotations. Two problems had been identified to achieve this method. The first problem relates to splitting the single monolithic Gene Ontology RDF/XML file into a set of smaller files that can be easy to assess and process. Thus, these files can be enriched with protein sequences and Inferred from Electronic Annotation evidence associations. The second problem involves searching for a set of semantically similar Gene Ontology terms to a given query. The details of macro and micro problems involved and their solutions including objective of this study are described. This paper also describes the protein sequence annotation and the Gene Ontology. The methodology of this study and Gene Ontology based protein sequence annotation tool namely extended UTMGO is presented. Furthermore, its basic version which is a Gene Ontology browser that is based on semantic similarity search is also introduced.

Keywords: automatic clustering, bioinformatics tool, gene ontology, protein sequence annotation, semantic similarity search

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Authors: Panpan Xu, Shulin Sui, Zongjie Du

Abstract:

Genetic algorithm is widely used in optimization problems for its excellent global search capabilities and highly parallel processing capabilities; but, it converges prematurely and has a poor local optimization capability in actual operation. Simulated annealing algorithm can avoid the search process falling into local optimum. A hybrid genetic algorithm based on simulated annealing is designed by combining the advantages of genetic algorithm and simulated annealing algorithm. The numerical experiment represents the hybrid genetic algorithm can be applied to solve the function optimization problems efficiently.

Keywords: Genetic algorithm, Simulated annealing, Hybrid genetic algorithm, Function optimization.

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Authors: T. Manzur, S. Iffat, M. A. Noor

Abstract:

In this paper, relationship between different properties of IC concrete and water cement ratio, obtained from a comprehensive experiment conducted on IC using local materials (Burnt clay chips- BC) is presented. In addition, saturated SAP was used as an IC material in some cases. Relationships have been developed through regression analysis. The focus of this analysis is on developing relationship between a dependent variable and an independent variable. Different percent replacements of BC and water cement ratios were used. Compressive strength, modulus of elasticity, water permeability and chloride permeability were tested and variations of these parameters were analyzed with respect to water cement ratio.

Keywords: Compressive strength, concrete, curing, lightweight, aggregate, superabsorbent polymer, internal curing.

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Authors: U. Chattaraj, K. Dhusiya, M. Raviteja

Abstract:

Perception reaction time of drivers is an outcome of human thought process, which is vague and approximate in nature and also varies from driver to driver. So, in this study a fuzzy logic based model for prediction of the same has been presented, which seems suitable. The control factors, like, age, experience, intensity of driving of the driver, speed of the vehicle and distance of stimulus have been considered as premise variables in the model, in which the perception reaction time is the consequence variable. Results show that the model is able to explain the impacts of the control factors on perception reaction time properly.

Keywords: Driver, fuzzy logic, perception reaction time, premise variable.

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Authors: Gayadhar Panda, Sidhartha Panda, C. Ardil

Abstract:

A modified Genetic Algorithm (GA) based optimal selection of parameters for Automatic Generation Control (AGC) of multi-area electric energy systems is proposed in this paper. Simulations on multi-area reheat thermal system with and without consideration of nonlinearity like governor dead band followed by 1% step load perturbation is performed to exemplify the optimum parameter search. In this proposed method, a modified Genetic Algorithm is proposed where one point crossover with modification is employed. Positional dependency in respect of crossing site helps to maintain diversity of search point as well as exploitation of already known optimum value. This makes a trade-off between exploration and exploitation of search space to find global optimum in less number of generations. The proposed GA along with decomposition technique as developed has been used to obtain the optimum megawatt frequency control of multi-area electric energy systems. Time-domain simulations are conducted with trapezoidal integration along with decomposition technique. The superiority of the proposed method over existing one is verified from simulations and comparisons.

Keywords: Automatic Generation Control (AGC), Reheat, Proportional Integral (PI) controller, Dead Band, Genetic Algorithm(GA).

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Authors: Abder-Rahman Ali, Antoine Vacavant, Manuel Grand-Brochier, Adélaïde Albouy-Kissi, Jean-Yves Boire

Abstract:

In this paper, we present a new segmentation approach for liver lesions in regions of interest within MRI (Magnetic Resonance Imaging). This approach, based on a two-cluster Fuzzy CMeans methodology, considers the parameter variable compactness to handle uncertainty. Fine boundaries are detected by a local recursive merging of ambiguous pixels with a sequential forward floating selection with Zernike moments. The method has been tested on both synthetic and real images. When applied on synthetic images, the proposed approach provides good performance, segmentations obtained are accurate, their shape is consistent with the ground truth, and the extracted information is reliable. The results obtained on MR images confirm such observations. Our approach allows, even for difficult cases of MR images, to extract a segmentation with good performance in terms of accuracy and shape, which implies that the geometry of the tumor is preserved for further clinical activities (such as automatic extraction of pharmaco-kinetics properties, lesion characterization, etc.).

Keywords: Defuzzification, floating search, fuzzy clustering, Zernike moments.

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Authors: Mohanad Alata, Mohammad Molhim, Abdullah Ramini

Abstract:

Fuzzy C-means Clustering algorithm (FCM) is a method that is frequently used in pattern recognition. It has the advantage of giving good modeling results in many cases, although, it is not capable of specifying the number of clusters by itself. In FCM algorithm most researchers fix weighting exponent (m) to a conventional value of 2 which might not be the appropriate for all applications. Consequently, the main objective of this paper is to use the subtractive clustering algorithm to provide the optimal number of clusters needed by FCM algorithm by optimizing the parameters of the subtractive clustering algorithm by an iterative search approach and then to find an optimal weighting exponent (m) for the FCM algorithm. In order to get an optimal number of clusters, the iterative search approach is used to find the optimal single-output Sugenotype Fuzzy Inference System (FIS) model by optimizing the parameters of the subtractive clustering algorithm that give minimum least square error between the actual data and the Sugeno fuzzy model. Once the number of clusters is optimized, then two approaches are proposed to optimize the weighting exponent (m) in the FCM algorithm, namely, the iterative search approach and the genetic algorithms. The above mentioned approach is tested on the generated data from the original function and optimal fuzzy models are obtained with minimum error between the real data and the obtained fuzzy models.

Keywords: Fuzzy clustering, Fuzzy C-Means, Genetic Algorithm, Sugeno fuzzy systems.

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