Search Results - (( using selection based algorithm ) OR ( basic optimization system algorithm ))
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1
Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…As the 50-50 probabilities for exploitation and exploration in the basic teaching learning-based optimization algorithm may be counterproductive, the Mamdani-type fuzzy inference system of the new algorithm takes these measures as a crisp inputs and generates selection as crisp output to choose either exploitation or exploration based on the current search requirement. …”
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2
System identification using Extended Kalman Filter
Published 2017“…Basically, Extended Kalman Filter (EKF) generally was known as the optimal estimator for a dynamic system. …”
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A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution
Published 2018“…The proposed algorithm is scrutinized and validated using the modified IEEE 30-bus test system. …”
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4
Development of cell formation algorithm and model for cellular manufacturing system
Published 2011“…Therefore, for this proposes good benchmarked algorithm, bacteria foraging algorithm is selected and developed to solve multiobjective cell formation model and traced constraints satisfaction handling to produce feasible optimal solution. …”
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5
A fuzzy case-based reasoning model for software requirements specifications quality assessment
Published 2023“…Additionally, for efficient cases retrieval in the CBR, relevant cases selection and nearest cases selection heuristic search algorithms are used in the system. …”
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An application of barnacles mating optimizer algorithm for combined economic and emission dispatch solution
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A simplified PID-like ANFIS controller trained by genetic algorithm to control nonlinear systems
Published 2010“…Moreover, the GA was used to find the optimal settings for the input and output scaling factors for this controller, instead of the widely used trial and error method. …”
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Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection
Published 2019“…Those problems lend themselves to the realm of optimization. Considering the wide success of swarm intelligence methods in optimization problems, the main objective of this thesis is to contribute to the improvement of intrusion detection technology through the application of swarm-based optimization techniques to the basic problems of selecting optimal packet features, and optimal training of neural networks on classifying those features into normal and attack instances. …”
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9
Classification of herbs plant diseases via hierarchical dynamic artificial neural network
Published 2010“…Once the image of a target is captured digitally, a myriad of image processing algorithms can be used to extract features from it. …”
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INTELLIGENT OPTIMIZATION OF INTERLINE POWER FLOW CONTROLLER IN TRANSMISSION SYSTEM
Published 2010“…The optimal parameters are derived to minimize the transmission line losses using three intelligent optimization techniques, namely Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Simulated Annealing (SA). …”
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11
Classification of herbs plant diseases via hierachical dynamic artificial neural network after image removal using kernel regression framework
Published 2011“…Once the image of a target is captured digitally, a myriad of image processing algorithms can be used to extract features from it. …”
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Optimal planning and design of hybrid renewable energy system for rural healthcare facilities / Olatomiwa Lanre Joseph
Published 2016“…Then, utilization of cost-effective optimization algorithm for optimal sizing of the energy resources and other system components with accurate mathematical models for energy management of the entire hybrid system. …”
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13
Application of hybrid intelligent systems in predicting the unconfined compressive strength of clay material mixed with recycled additive
Published 2021“…Actually, in these systems, respectively, the weights and biases of the artificial neural network (ANN) were optimized using the particle swarm optimization (PSO) and imperialism competitive algorithm (ICA) to get a higher accuracy compared to a pre-developed ANN model. …”
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Application of hybrid intelligent systems in predicting the unconfined compressive strength of clay material mixed with recycled additive
Published 2021“…Actually, in these systems, respectively, the weights and biases of the artificial neural network (ANN) were optimized using the particle swarm optimization (PSO) and imperialism competitive algorithm (ICA) to get a higher accuracy compared to a pre-developed ANN model. …”
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Catalytic conversion of methane and carbon dioxide in conventional fixed bed and dielectric barrier discharge plasma reactors
Published 2006“…Next, a hybrid Artificial Neural Network – Genetic Algorithm technique was used to facilitate modelling and optimization of the plasma reactor system for both non catalytic and catalytic dielectric barrier discharge plasma reactors. …”
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16
Satellite Image Segmentation Using Thresholding Technique
Published 2017“…The basic idea of automatic thresholding is to automatically select an optimal or several optimal grey-level threshold values for separating objects of interest in an image from the background based on their grey-level distribution. …”
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17
A Survey Of Supervised Machine Learning In Wireless Sensor Network: A Power Management Perspective
Published 2013“…This survey paper is focused on the discussion of best optimal path routing algorithms in wireless sensor networks by using supervised machine learning approaches. …”
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18
An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming
Published 2018“…Basically,one important issue in the power system network is to provide the optimal Economic Load Dispatch (ELD) solution in order to guarantee the sustainable consumer load demand.However,today ELD solution is essential to include together with the environmental aspect and known as Environmental Economic Load Dispatch (EELD).For that reason, many researchers continue in the development of new simulation tool specifically to overcome the EELD problems.Therefore,this study prepared an improved hybrid metaheuristic technique named as New Meta Heuristic Evolutionary Programming (NMEP) to provide the best possible solution in solving the identified single objective and multi objective functions for EELD solution.This new technique a merging cloning strategy that involved in an Artificial Immune System (AIS) algorithm into algorithm of Meta Heuristic Evolutionary Programming (Meta-EP).The development of NMEP technique is to minimize total cost,reduce the total emission during generator operation through the common formula in EELD and lowest total system loss.Besides that,all mentioned objective functions were also optimized together simultaneously that formulated using the weighted sum method before had been executed on the multi objective NMEP or called MONMEP.Both individual and multi objective NMEP techniques performance were verified among other two common heuristic methods known as AIS and Meta-EP techniques.In addition,the best possible solution defined using the aggregate function method.Through this method,the selection of the best MOEELD solution became effortless as compared with MO individually that required compare two or more objective function in one time manually.Among those three optimization techniques the lowest total aggregate values mostly resulted via the NMEP technique.Based upon that,the proposed technique is proving as the outstanding method compared with Meta-EP and AIS techniques in solving the EELD problem for both standard IEEE 26 bus and 57 bus systems.…”
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A phonetically rich and balanced lexical corpus using zipfian distribution for an under resourced language / Aminath Farshana
Published 2018“…The performance of the proposed method was also evaluated by comparing the results with an existing benchmark method (greedy algorithm). The results show that the sentences selected using proposed method cover all the phonetic units and is 14 times smaller than the corpus developed using the benchmark method. …”
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Enhanced Mobility Solution In Mobile Ipv6 Network
Published 2008“…The interface selection algorithm was based on NEMO implementation structure using a technique of mutihoming which was extended to MIPv6 concepts The outcome of this research work are: a designed policy protocol for policy messages communication between the Mobile Router and the Home Agent, the framework is simulated using Network Simulator (NS2) with an extension of mobiwan, the result shows the end to end delay, average end to end delay, overhead, optimal routing path, average inter-packet latency and throughput of the developed system. …”
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