Search results for: Distributed Artificial Intelligence

Authors: A. Greco, N. Mammone, F.C. Morabito, M.Versaci

Abstract:

This paper is mainly concerned with the application of a novel technique of data interpretation to the characterization and classification of measurements of plasma columns in Tokamak reactors for nuclear fusion applications. The proposed method exploits several concepts derived from soft computing theory. In particular, Artifical Neural Networks have been exploited to classify magnetic variables useful to determine shape and position of the plasma with a reduced computational complexity. The proposed technique is used to analyze simulated databases of plasma equilibria based on ITER geometry configuration. As well as demonstrating the successful recovery of scalar equilibrium parameters, we show that the technique can yield practical advantages compares with earlier methods.

Keywords: Tokamak, sensors, artificial neural network.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1827

Authors: Firas M. Tuaimah

Abstract:

This paper presents an Artificial Neural Network based approach for short-term load forecasting and exactly for two days ahead. Two seasons have been discussed for Iraqi power system, namely summer and winter; the hourly load demand is the most important input variables for ANN based load forecasting. The recorded daily load profile with a lead time of 1-48 hours for July and December of the year 2012 was obtained from the operation and control center that belongs to the Ministry of Iraqi electricity.

The results of the comparison show that the neural network gives a good prediction for the load forecasting and for two days ahead.

Keywords: Short-Term Load Forecasting, Artificial Neural Networks, Back propagation learning.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1563

Authors: Alexandru George Floares

Abstract:

Chronic hepatitis B can evolve to cirrhosis and liver cancer. Interferon is the only effective treatment, for carefully selected patients, but it is very expensive. Some of the selection criteria are based on liver biopsy, an invasive, costly and painful medical procedure. Therefore, developing efficient non-invasive selection systems, could be in the patients benefit and also save money. We investigated the possibility to create intelligent systems to assist the Interferon therapeutical decision, mainly by predicting with acceptable accuracy the results of the biopsy. We used a knowledge discovery in integrated medical data - imaging, clinical, and laboratory data. The resulted intelligent systems, tested on 500 patients with chronic hepatitis B, based on C5.0 decision trees and boosting, predict with 100% accuracy the results of the liver biopsy. Also, by integrating the other patients selection criteria, they offer a non-invasive support for the correct Interferon therapeutic decision. To our best knowledge, these decision systems outperformed all similar systems published in the literature, and offer a realistic opportunity to replace liver biopsy in this medical context.

Keywords: Interferon, chronic hepatitis B, intelligent virtualbiopsy.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1466

Authors: Kanhu Charan Bhuyan, Subhransu Padhee, Rajesh Kumar Patjoshi, Kamalakanta Mahapatra

Abstract:

Fuel cell is an emerging technology in the field of renewable energy sources which has the capacity to replace conventional energy generation sources. Fuel cell utilizes hydrogen energy to produce electricity. The electricity generated by the fuel cell can’t be directly used for a specific application as it needs proper power conditioning. Moreover, the output power fluctuates with different operating conditions. To get a stable output power at an economic rate, power conditioning circuit is essential for fuel cell. This paper implements a two-staged power conditioning unit for fuel cell based distributed generation using hysteresis current control technique.

Keywords: Fuel cell, power conditioning unit, hysteresis control.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2432

Authors: Chansheng He, Carlo DeMarchi

Abstract:

A physically based, spatially-distributed water quality model is being developed to simulate spatial and temporal distributions of material transport in the Great Lakes Watersheds of the U.S. Multiple databases of meteorology, land use, topography, hydrography, soils, agricultural statistics, and water quality were used to estimate nonpoint source loading potential in the study watersheds. Animal manure production was computed from tabulations of animals by zip code area for the census years of 1987, 1992, 1997, and 2002. Relative chemical loadings for agricultural land use were calculated from fertilizer and pesticide estimates by crop for the same periods. Comparison of these estimates to the monitored total phosphorous load indicates that both point and nonpoint sources are major contributors to the total nutrient loads in the study watersheds, with nonpoint sources being the largest contributor, particularly in the rural watersheds. These estimates are used as the input to the distributed water quality model for simulating pollutant transport through surface and subsurface processes to Great Lakes waters. Visualization and GIS interfaces are developed to visualize the spatial and temporal distribution of the pollutant transport in support of water management programs.

Keywords: Distributed Large Basin Runoff Model, Great LakesWatersheds, nonpoint source pollution, and point sources.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1540

Authors: H. Khorashadi-Zadeh, M. R. Aghaebrahimi

Abstract:

A novel application of neural network approach to fault classification and fault location of Medium voltage cables is demonstrated in this paper. Different faults on a protected cable should be classified and located correctly. This paper presents the use of neural networks as a pattern classifier algorithm to perform these tasks. The proposed scheme is insensitive to variation of different parameters such as fault type, fault resistance, and fault inception angle. Studies show that the proposed technique is able to offer high accuracy in both of the fault classification and fault location tasks.

Keywords: Artificial neural networks, cable, fault location andfault classification.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1856

Authors: Anjum Iqbal, Mohd Aizaini Maarof

Abstract:

Artificial Immune System (AIS) is relatively naive paradigm for intelligent computations. The inspiration for AIS is derived from natural Immune System (IS). Classically it is believed that IS strives to discriminate between self and non-self. Most of the existing AIS research is based on this approach. Danger Theory (DT) argues this approach and proposes that IS fights against danger producing elements and tolerates others. We, the computational researchers, are not concerned with the arguments among immunologists but try to extract from it novel abstractions for intelligent computation. This paper aims to follow DT inspiration for intelligent data processing. The approach may introduce new avenue in intelligent processing. The data used is system calls data that is potentially significant in intrusion detection applications.

Keywords: artificial immune system, danger theory, intelligent processing, system calls

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1892

Authors: A. Hossain, A. S. W. Kurny

Abstract:

The factors necessary to obtain an optimal heat treatment that influence the hardness and resistivity of Al-6Si-0.5Mg casting alloys with Cu or/and Ni additions were investigated. The alloys were homogenised (24hr at 500^oC), solutionized (2hr at 540^oC) and artificially ageing at various times and temperatures. The alloys were aged isochronally for 60 minutes at temperatures up to 400^oC and isothermally at 150, 175, 200, 225, 250 & 300^oC for different periods in the range 15 to 360 minutes. The hardness and electrical resistivity of the alloys were measured for various artificial ageing times and temperatures. From the isochronal ageing treatment, hardness found maximum ageing at 225^oC. And from the isothermal ageing treatment, hardness found maximum for 60 minutes at 225^oC. So the optimal heat treatment consists of 60 minutes ageing at 225^oC.

Keywords: Ageing, Al-Si-Mg alloy, hardness, resistivity.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3073

Authors: H. P. Singh, S. Singh

Abstract:

The voice signal in Voice over Internet protocol (VoIP) system is processed through the best effort policy based IP network, which leads to the network degradations including delay, packet loss jitter. The work in this paper presents the implementation of finite impulse response (FIR) filter for voice quality improvement in the VoIP system through distributed arithmetic (DA) algorithm. The VoIP simulations are conducted with AMR-NB 6.70 kbps and G.729a speech coders at different packet loss rates and the performance of the enhanced VoIP signal is evaluated using the perceptual evaluation of speech quality (PESQ) measurement for narrowband signal. The results show reduction in the computational complexity in the system and significant improvement in the quality of the VoIP voice signal.

Keywords: VoIP, Signal Quality, Distributed Arithmetic, Packet Loss, Speech Coder.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1837

Authors: C. lo Storto

Abstract:

This paper presents an approach based on the adoption of a distributed cognition framework and a non parametric multicriteria evaluation methodology (DEA) designed specifically to compare e-commerce websites from the consumer/user viewpoint. In particular, the framework considers a website relative efficiency as a measure of its quality and usability. A website is modelled as a black box capable to provide the consumer/user with a set of functionalities. When the consumer/user interacts with the website to perform a task, he/she is involved in a cognitive activity, sustaining a cognitive cost to search, interpret and process information, and experiencing a sense of satisfaction. The degree of ambiguity and uncertainty he/she perceives and the needed search time determine the effort size – and, henceforth, the cognitive cost amount – he/she has to sustain to perform his/her task. On the contrary, task performing and result achievement induce a sense of gratification, satisfaction and usefulness. In total, 9 variables are measured, classified in a set of 3 website macro-dimensions (user experience, site navigability and structure). The framework is implemented to compare 40 websites of businesses performing electronic commerce in the information technology market. A questionnaire to collect subjective judgements for the websites in the sample was purposely designed and administered to 85 university students enrolled in computer science and information systems engineering undergraduate courses.

Keywords: Website, e-commerce, DEA, distributed cognition, evaluation, comparison.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1712

Authors: Nhon Do, Hien Nguyen

Abstract:

Nowadays there are many methods for representing knowledge such as semantic network, neural network, and conceptual graphs. Nonetheless, these methods are not sufficiently efficient when applied to perform and deduce on knowledge domains about supporting in general education such as algebra, analysis or plane geometry. This leads to the introduction of computational network which is a useful tool for representation knowledge base, especially for computational knowledge, especially knowledge domain about general education. However, when dealing with a practical problem, we often do not immediately find a new solution, but we search related problems which have been solved before and then proposing an appropriate solution for the problem. Besides that, when finding related problems, we have to determine whether the result of them can be used to solve the practical problem or not. In this paper, the extension model of computational network has been presented. In this model, Sample Problems, which are related problems, will be used like the experience of human about practical problem, simulate the way of human thinking, and give the good solution for the practical problem faster and more effectively. This extension model is applied to construct an automatic system for solving algebraic problems in middle school.

Keywords: educational software, artificial intelligence, knowledge base system, knowledge representation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1680

Authors: Mughal Yar M, Israr Ul Haq, Bushra Noman

Abstract:

The stem cells have ability to differentiated themselves through mitotic cell division and various range of specialized cell types. Cellular differentiation is a way by which few specialized cell develops into more specialized.This paper studies the fundamental problem of computational schema for an artificial neural network based on chemical, physical and biological variables of state. By doing this type of study system could be model for a viable propagation of various economically important stem cells differentiation. This paper proposes various differentiation outcomes of artificial neural network into variety of potential specialized cells on implementing MATLAB version 2009. A feed-forward back propagation kind of network was created to input vector (five input elements) with single hidden layer and one output unit in output layer. The efficiency of neural network was done by the assessment of results achieved from this study with that of experimental data input and chosen target data. The propose solution for the efficiency of artificial neural network assessed by the comparatative analysis of “Mean Square Error" at zero epochs. There are different variables of data in order to test the targeted results.

Keywords: Computational shcmin, meiosis, mitosis, neuralnetwork, Stem cell SOM;

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1512

Authors: Farzaneh Ahmadzadeh

Abstract:

Quality control charts are very effective in detecting out of control signals but when a control chart signals an out of control condition of the process mean, searching for a special cause in the vicinity of the signal time would not always lead to prompt identification of the source(s) of the out of control condition as the change point in the process parameter(s) is usually different from the signal time. It is very important to manufacturer to determine at what point and which parameters in the past caused the signal. Early warning of process change would expedite the search for the special causes and enhance quality at lower cost. In this paper the quality variables under investigation are assumed to follow a multivariate normal distribution with known means and variance-covariance matrix and the process means after one step change remain at the new level until the special cause is being identified and removed, also it is supposed that only one variable could be changed at the same time. This research applies artificial neural network (ANN) to identify the time the change occurred and the parameter which caused the change or shift. The performance of the approach was assessed through a computer simulation experiment. The results show that neural network performs effectively and equally well for the whole shift magnitude which has been considered.

Keywords: Artificial neural network, change point estimation, monte carlo simulation, multivariate exponentially weighted movingaverage

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1387

Authors: Ebtehal Alawi Alsaggaf, Shehab A. Gamalel-Din

Abstract:

Exploring an autistic child in Elementary school is a difficult task that must be fully thought out and the teachers should be aware of the many challenges they face raising their child especially the behavioral problems of autistic children. Hence there arises a need for developing Artificial intelligence (AI) Contemporary Techniques to help diagnosis to discover autistic people. In this research, we suggest designing architecture of expert system that combine Cognitive Maps (CM) with Case Based Reasoning technique (CBR) in order to reduce time and costs of traditional diagnosis process for the early detection to discover autistic children. The teacher is supposed to enter child's information for analyzing by CM module. Then, the reasoning processor would translate the output into a case to be solved a current problem by CBR module. We will implement a prototype for the model as a proof of concept using java and MYSQL. This will be provided a new hybrid approach that will achieve new synergies and improve problem solving capabilities in AI. And we will predict that will reduce time, costs, the number of human errors and make expertise available to more people who want who want to serve autistic children and their families.

Keywords: Autism, Cognitive Maps (CM), Case Based Reasoning technique (CBR).

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1967

Authors: Shuen-Tai Wang, Ying-Chuan Chen, Hsi-Ya Chang

Abstract:

The rapid improvement of the microprocessor and network has made it possible for the PC cluster to compete with conventional supercomputers. Lots of high throughput type of applications can be satisfied by using the current desktop PCs, especially for those in PC classrooms, and leave the supercomputers for the demands from large scale high performance parallel computations. This paper presents our development on enabling an automated deployment mechanism for cluster computing to utilize the computing power of PCs such as reside in PC classroom. After well deployment, these PCs can be transformed into a pre-configured cluster computing resource immediately without touching the existing education/training environment installed on these PCs. Thus, the training activities will not be affected by this additional activity to harvest idle computing cycles. The time and manpower required to build and manage a computing platform in geographically distributed PC classrooms also can be reduced by this development.

Keywords: PC cluster, automated deployment, cluster computing, PC classroom.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1535

Authors: Abeer Samy, Oliver C. Saavedra Valeriano, Abdelazim Negm

Abstract:

The Blue Nile Basin is the most important tributary of the Nile River. Egypt and Sudan are almost dependent on water originated from the Blue Nile. This multi-dependency creates conflicts among the three countries Egypt, Sudan, and Ethiopia making the management of these conflicts as an international issue. Good assessment of the water resources of the Blue Nile is an important to help in managing such conflicts. Hydrological models are good tool for such assessment. This paper presents a critical review of the nature and variability of the climate and hydrology of the Blue Nile Basin as a first step of using hydrological modeling to assess the water resources of the Blue Nile. Many several attempts are done to develop basin-scale hydrological modeling on the Blue Nile. Lumped and semi distributed models used averages of meteorological inputs and watershed characteristics in hydrological simulation, to analyze runoff for flood control and water resource management. Distributed models include the temporal and spatial variability of catchment conditions and meteorological inputs to allow better representation of the hydrological process. The main challenge of all used models was to assess the water resources of the basin is the shortage of the data needed for models calibration and validation. It is recommended to use distributed model for their higher accuracy to cope with the great variability and complexity of the Blue Nile basin and to collect sufficient data to have more sophisticated and accurate hydrological modeling.

Keywords: Blue Nile Basin, Climate Change, Hydrological Modeling, Watershed.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3079

Authors: Hermann Kuehnle

Abstract:

Applications of the Hausdorff space and its mappings into tangent spaces are outlined, including their fractal dimensions and self-similarities. The paper details this theory set up and further describes virtualizations and atomization of manufacturing processes. It demonstrates novel concurrency principles that will guide manufacturing processes and resources configurations. Moreover, varying levels of details may be produced by up folding and breaking down of newly introduced generic models. This choice of layered generic models for units and systems aspects along specific aspects allows research work in parallel to other disciplines with the same focus on all levels of detail. More credit and easier access are granted to outside disciplines for enriching manufacturing grounds. Specific mappings and the layers give hints for chances for interdisciplinary outcomes and may highlight more details for interoperability standards, as already worked on the international level. The new rules are described, which require additional properties concerning all involved entities for defining distributed decision cycles, again on the base of self-similarity. All properties are further detailed and assigned to a maturity scale, eventually displaying the smartness maturity of a total shopfloor or a factory. The paper contributes to the intensive ongoing discussion in the field of intelligent distributed manufacturing and promotes solid concepts for implementations of Cyber Physical Systems and the Internet of Things into manufacturing industry, like industry 4.0, as discussed in German-speaking countries.

Keywords: Autonomous unit, Networkability, Smart manufacturing unit, Virtualization.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2077

Authors: K. Raghuwaiya, B. Sharma, J. Vanualailai

Abstract:

This paper presents a set of artificial potential field functions that improves upon, in general, the motion planning and posture control, with theoretically guaranteed point and posture stabilities, convergence and collision avoidance properties of the general3-trailer system in a priori known environment. We basically design and inject two new concepts; ghost walls and the distance optimization technique (DOT) to strengthen point and posture stabilities, in the sense of Lyapunov, of our dynamical model. This new combination of techniques emerges as a convenient mechanism for obtaining feasible orientations at the target positions with an overall reduction in the complexity of the navigation laws. Simulations are provided to demonstrate the effectiveness of the controls laws.

Keywords: Artificial potential fields, 3-trailer systems, motion planning, posture.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2159

Authors: Nafe Moradkhani, Frederick Benaben, Benoit Montreuil, Ali Vatankhah Barenji, Dima Nazzal

Abstract:

In the context of the global pandemic, the practical management of the 2020 presidential election in the USA was a strong concern. To anticipate and prepare for this election accurately, one of the main challenges was to confront: (i) forecasts of voter turnout, (ii) capacities of the facilities and, (iii) potential configuration options of resources. The approach chosen to conduct this anticipative study consists of collecting data about forecasts and using simulation models to work simultaneously on resource allocation and facility configuration of polling places in Fulton County, Georgia’s largest county. This article presents the results of the simulations of such places facing pre-identified potential risks. These results are oriented towards the efficiency of these places according to different criteria (health, trust, comfort). Then a dynamic framework is introduced to describe risks as physical forces perturbing the efficiency of the observed system. Finally, the main benefits and contributions resulting from this simulation campaign are presented.

Keywords: performance, decision support, simulation, artificial intelligence, risk management, election, pandemics, information system

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 656

Authors: José Neves, M. Rosário Martins, Fátima Candeias, Diana Ferreira, Sílvia Arantes, Júlio Cruz-Morais, Guida Gomes, Joaquim Macedo, António Abelha, Henrique Vicente

Abstract:

Some plants of genus Schinus have been used in the folk medicine as topical antiseptic, digestive, purgative, diuretic, analgesic or antidepressant, and also for respiratory and urinary infections. Chemical composition of essential oils of S. molle and S. terebinthifolius had been evaluated and presented high variability according with the part of the plant studied and with the geographic and climatic regions. The pharmacological properties, namely antimicrobial, anti-tumoural and anti-inflammatory activities are conditioned by chemical composition of essential oils. Taking into account the difficulty to infer the pharmacological properties of Schinus essential oils without hard experimental approach, this work will focus on the development of a decision support system, in terms of its knowledge representation and reasoning procedures, under a formal framework based on Logic Programming, complemented with an approach to computing centered on Artificial Neural Networks and the respective Degree-of-Confidence that one has on such an occurrence.

Keywords: Artificial neuronal networks, essential oils, knowledge representation and reasoning, logic programming, Schinus molle L, Schinus terebinthifolius raddi.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2424

Authors: Djalal Eddine Khodja, Boukhemis Chetate

Abstract:

In this paper, an automatic system of diagnosis was developed to detect and locate in real time the defects of the wound rotor asynchronous machine associated to electronic converter. For this purpose, we have treated the signals of the measured parameters (current and speed) to use them firstly, as indicating variables of the machine defects under study and, secondly, as inputs to the Artificial Neuron Network (ANN) for their classification in order to detect the defect type in progress. Once a defect is detected, the interpretation system of information will give the type of the defect and its place of appearance.

Keywords: Artificial Neuron Networks (ANN), Effective Value (RMS), Experimental results, Failure detection Indicating values, Motor-converter unit.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1505

Authors: Wael M. El-Mamlouk, Metwally A. El-Sharkawy, Hossam. E. Mostafa

Abstract:

In this paper, we analyze and test a scheme for the estimation of electrical fundamental frequency signals from the harmonic load current and voltage signals. The scheme was based on using two different Multi Layer Artificial Neural Networks (ML-ANN) one for the current and the other for the voltage. This study also analyzes and tests the effect of choosing the optimum artificial neural networks- sizes which determine the quality and accuracy of the estimation of electrical fundamental frequency signals. The simulink tool box of the Matlab program for the simulation of the test system and the test of the neural networks has been used.

Keywords: Harmonics, Neural Networks, Modeling, Simulation, Active filters, electric Networks.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1601

Authors: Cuneyt Yucelbas, Seral Ozsen, Sule Yucelbas, Gulay Tezel

Abstract:

Due to the fact that there exist only a small number of complex systems in artificial immune system (AIS) that work out nonlinear problems, nonlinear AIS approaches, among the well-known solution techniques, need to be developed. Gaussian function is usually used as similarity estimation in classification problems and pattern recognition. In this study, diagnosis of breast cancer, the second type of the most widespread cancer in women, was performed with different distance calculation functions that euclidean, gaussian and gaussian-euclidean hybrid function in the clonal selection model of classical AIS on Wisconsin Breast Cancer Dataset (WBCD), which was taken from the University of California, Irvine Machine-Learning Repository. We used 3-fold cross validation method to train and test the dataset. According to the results, the maximum test classification accuracy was reported as 97.35% by using of gaussian-euclidean hybrid function for fold-3. Also, mean of test classification accuracies for all of functions were obtained as 94.78%, 94.45% and 95.31% with use of euclidean, gaussian and gaussian-euclidean, respectively. With these results, gaussian-euclidean hybrid function seems to be a potential distance calculation method, and it may be considered as an alternative distance calculation method for hard nonlinear classification problems.

Keywords: Artificial Immune System, Breast Cancer Diagnosis, Euclidean Function, Gaussian Function.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2126

Authors: Dariush Jafari, S. Mostafa Nowee

Abstract:

In this study a ternary system containing sodium chloride as solute, water as primary solvent and ethanol as the antisolvent was considered to investigate the application of artificial neural network (ANN) in prediction of sodium solubility in the mixture of water as the solvent and ethanol as the antisolvent. The system was previously studied using by Extended UNIQUAC model by the authors of this study. The comparison between the results of the two models shows an excellent agreement between them (R2=0.99), and also approves the capability of ANN to predict the thermodynamic behavior of ternary electrolyte systems which are difficult to model.

Keywords: Thermodynamic modeling, ANN, solubility, ternary electrolyte system.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2159

Authors: Mu-Yen Chen, Min-Hsuan Fan, Chia-Chen Chen, Siang-Yu Jhong

Abstract:

In recent years, real estate prediction or valuation has been a topic of discussion in many developed countries. Improper hype created by investors leads to fluctuating prices of real estate, affecting many consumers to purchase their own homes. Therefore, scholars from various countries have conducted research in real estate valuation and prediction. With the back-propagation neural network that has been popular in recent years and the orthogonal array in the Taguchi method, this study aimed to find the optimal parameter combination at different levels of orthogonal array after the system presented different parameter combinations, so that the artificial neural network obtained the most accurate results. The experimental results also demonstrated that the method presented in the study had a better result than traditional machine learning. Finally, it also showed that the model proposed in this study had the optimal predictive effect, and could significantly reduce the cost of time in simulation operation. The best predictive results could be found with a fewer number of experiments more efficiently. Thus users could predict a real estate transaction price that is not far from the current actual prices.

Keywords: Artificial Neural Network, Taguchi Method, Real Estate Valuation Model.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3073

Authors: C. Ardil

Abstract:

Unmanned combat aircraft (UCA) are expanding significantly in several defense industries, along with artificial intelligence improvements in highly precise technology. UCA is crucial in military settings for targeting enemy elements, and objects. UCA is also utilized for highly precise reconnaissance and surveillance tasks. To select the best alternative for critical missions, a methodical and effective strategy for UCA selection is required. Multiple criteria decision-making (MCDM) methodologies are ideally equipped to handle the complexity of alternative aircraft selection. To analyze UCA alternatives for the selection process, an integrated methodology built on the objective criteria weights and preference analysis for reference ideal solution (PARIS). First, the weights of essential elements are determined using the average weight (AW), standard deviation (SW) and entropy weight (EW) approach. The weights of the evaluation criteria affect the decision-making process. The aircraft choices in the decision problem are then ranked using objective criteria weights along with the PARIS technique. The validation and sensitivity analysis of the proposed MCDM approach are discussed.

Keywords: unmanned combat aircraft (UCA), multiple criteria decision making, MCDM, PARIS

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 494

Authors: Ghada Elshafei, Abdelazim Negm

Abstract:

Recently, the green architecture becomes a significant way to a sustainable future. Green building designs involve finding the balance between comfortable homebuilding and sustainable environment. Moreover, the utilization of the new technologies such as artificial intelligence techniques are used to complement current practices in creating greener structures to keep the built environment more sustainable. The most common objectives in green buildings should be designed to minimize the overall impact of the built environment that effect on ecosystems in general and in particularly human health and natural environment. This will lead to protecting occupant health, improving employee productivity, reducing pollution and sustaining the environmental. In green building design, multiple parameters which may be interrelated, contradicting, vague and of qualitative/quantitative nature are broaden to use. This paper presents a comprehensive critical state- ofart- review of current practices based on fuzzy and its combination techniques. Also, presented how green architecture/building can be improved using the technologies that been used for analysis to seek optimal green solutions strategies and models to assist in making the best possible decision out of different alternatives.

Keywords: Green architecture/building, technologies, optimization, strategies, fuzzy techniques and models.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2527

Authors: Abhishek Swaroop, Awadhesh Kumar Singh

Abstract:

The group mutual exclusion (GME) problem is a variant of the mutual exclusion problem. In the present paper a token-based group mutual exclusion algorithm, capable of handling transient faults, is proposed. The algorithm uses the concept of dynamic request sets. A time out mechanism is used to detect the token loss; also, a distributed scheme is used to regenerate the token. The worst case message complexity of the algorithm is n+1. The maximum concurrency and forum switch complexity of the algorithm are n and min (n, m) respectively, where n is the number of processes and m is the number of groups. The algorithm also satisfies another desirable property called smooth admission. The scheme can also be adapted to handle the extended group mutual exclusion problem.

Keywords: Dynamic request sets, Fault tolerance, Smoothadmission, Transient faults.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1679

Authors: Tatsuya Kasuga, Hidehisa Shimada, Kimio Oguchi

Abstract:

Recent rapid progress in ICT (Information and Communication Technology) has advanced the penetration of sensor networks (SNs) and their attractive applications. Agriculture is one of the fields well able to benefit from ICT. Plant factories control several parameters related to plant growth in closed areas such as air temperature, humidity, water, culture medium concentration, and artificial lighting by using computers and AI (Artificial Intelligence) is being researched in order to obtain stable and safe production of vegetables and medicinal plants all year anywhere, and attain self-sufficiency in food. By providing isolation from the natural environment, a plant factory can achieve higher productivity and safe products. However, the biggest issue with plant factories is the return on investment. Profits are tenuous because of the large initial investments and running costs, i.e. electric power, incurred. At present, LED (Light Emitting Diode) lights are being adopted because they are more energy-efficient and encourage photosynthesis better than the fluorescent lamps used in the past. However, further cost reduction is essential. This paper introduces experiments that reveal which color of LED lighting best enhances the growth of cultured radish sprouts. Radish sprouts were cultivated in the experimental environment formed by a hydroponics kit with three cultivation shelves (28 samples per shelf) each with an artificial lighting rack. Seven LED arrays of different color (white, blue, yellow green, green, yellow, orange, and red) were compared with a fluorescent lamp as the control. Lighting duration was set to 12 hours a day. Normal water with no fertilizer was circulated. Seven days after germination, the length, weight and area of leaf of each sample were measured. Electrical power consumption for all lighting arrangements was also measured. Results and discussions: As to average sample length, no clear difference was observed in terms of color. As regards weight, orange LED was less effective and the difference was significant (p < 0.05). As to leaf area, blue, yellow and orange LEDs were significantly less effective. However, all LEDs offered higher productivity per W consumed than the fluorescent lamp. Of the LEDs, the blue LED array attained the best results in terms of length, weight and area of leaf per W consumed. Conclusion and future works: An experiment on radish sprout cultivation under 7 different color LED arrays showed no clear difference in terms of sample size. However, if electrical power consumption is considered, LEDs offered about twice the growth rate of the fluorescent lamp. Among them, blue LEDs showed the best performance. Further cost reduction e.g. low power lighting remains a big issue for actual system deployment. An automatic plant monitoring system with sensors is another study target.

Keywords: Electric power consumption, LED color, LED lighting, plant factory.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1360

Authors: Ali Reza Tahavvor, Saeed Hosseini, Nazli Jowkar, Afshin Karimzadeh Fard

Abstract:

Experimental & numeral study of temperature distribution during milling process, is important in milling quality and tools life aspects. In the present study the milling cross-section temperature is determined by using Artificial Neural Networks (ANN) according to the temperature of certain points of the work piece and the point specifications and the milling rotational speed of the blade. In the present work, at first three-dimensional model of the work piece is provided and then by using the Computational Heat Transfer (CHT) simulations, temperature in different nods of the work piece are specified in steady-state conditions. Results obtained from CHT are used for training and testing the ANN approach. Using reverse engineering and setting the desired x, y, z and the milling rotational speed of the blade as input data to the network, the milling surface temperature determined by neural network is presented as output data. The desired points temperature for different milling blade rotational speed are obtained experimentally and by extrapolation method for the milling surface temperature is obtained and a comparison is performed among the soft programming ANN, CHT results and experimental data and it is observed that ANN soft programming code can be used more efficiently to determine the temperature in a milling process.

Keywords: Milling process, rotational speed, Artificial Neural Networks, temperature.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2337