Search Results - (( weight distribution (search OR research) algorithm ) OR ( parameter evaluation case algorithm ))

Improved gravitational search algorithm for optimal placement and sizing of distributed generation for power quality enhancement by Daud, Sa'adah

“…The optimization problem is generated using a weighted sum method. In order to obtain the best compromise solution, a novel heuristic algorithm based on improved gravitational search algorithm (IGSA) is proposed as an optimization technique. …”
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An experience oriented-convergence improved gravitational search algorithm for minimum variance distortionless response beamforming optimum by Darzi S., Tiong S.K., Tariqul Islam M., Rezai Soleymanpour H., Kibria S.

An improved bat algorithm with artificial neural networks for classification problems by Rehman Gillani, Syed Muhammad Zubair

“…Metaheuristic search algorithms have been used for quite a while to optimally solve complex searching problems with ease. …”
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Optimal Location And Sizing Of Distrubuted Generator Using PSO And GA Algorithms In Power Systems by Hassan, Ayat Saleh

“…The multi-objective function, which represents the summation of product three indices by corresponding weights was utilized to identify the candidate buses to reduce the search space of the algorithm. …”
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Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network by Bujal, Noor Ropidah

“…However, there are no exact calculations behind the weight-sum method. On the other hand, this research proposes an Analytical Hierarchy Process (AHP) for obtaining more reliable weights (w1, w2, w3) or coefficient factors based on priority rank. …”
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Enhanced Cuckoo Search Algorithm With Metaheuristic Components For Extracting The Maxima Of The Orientation Distribution Function by Shehab, Mohammad Mohammad Said

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T-way testing : a test case generator based on melody search algorithm by Toh, Shu Yuen

“…Next, TTT-MS will be executed through main algorithms to generate Parameters Interaction List, Parameter Values Interaction List, and finally generate final Test Cases based on Melody Search Algorithm. …”
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A Hybrid Metaheuristic Technique Based on Grey Wolf Optimisation, Symbiotic Organism Search, and Ant Colony Optimisation for Solving Multi-Objective Vehicle Routing Problems by Ary, Maxsi

“…This study developed a hybrid metaheuristic algorithm involving grey wolf optimization, symbiotic organism search, and ant colony optimization (HMGSA) to address the multi-objective VRP. …”
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Short Text Classification Using An Enhanced Term Weighting Scheme And Filter-Wrapper Feature Selection by Alsmadi, Issa Mohammad Ibrahim

“…In the second stage, grey wolf optimization (GWO) algorithm, a new heuristic search algorithm, uses the SVM accuracy as a fitness function to find the optimal subset feature.…”
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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…Chemical Vapor Deposition (CVD) is the most efficient method for CNTs production.However,using CVD method encounters crucial issues such as customization,time and cost.Therefore,Response Surface Methodology (RSM) is proposed for modeling and the ABC-βHC is proposed for optimization purpose to address such issues.The selected CNTs characteristics are CNTs yield and quality represented by the ratio of the relative intensity of the D and G-bands (ID/IG).Six case studies are generated from collected dataset including four cases of CNTs yield and one case of ID/IG as single objective optimization problems,while the sixth case represents multi-objective problem.The input parameters of each case are a subset from the set of input parameters including reaction temperature,duration,carbon dioxide flow rate,methane partial pressure,catalyst loading,polymer weight and catalyst weight.The models for the first three case studies were mentioned in the original work.RSM is proposed to develop polynomial models for the output responses in the other three cases and to identi significant process parameters and interactions that could affect the CNTs output responses.The developed models are validated using t-test,correlation and pattern matching.The predictive results have a good agreement with the actual experimental data.The models are used as objective functions in optimization techniques.For multi-objective optimization,this study proposes Desirability Function Approach (DFA) to be integrated with other proposed algorithms to form hybrid techniques namely RSM-DFA,ABC-DFA and ABC-βHC-DFA.The proposed algorithms and other selected well-known algorithms are evaluated and compared on their CNTs yield and quality.The optimization results reveal that ABC-βHC and ABC-βHC-DFA obtained significant results in terms of success rate,required time,iterations,and function evaluations number compared to other well-known algorithms.Significantly,the optimization results from this study are better than the results from the original work of the collected dataset.…”
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Optimal location and size of distributed generation to reduce power losses and improve voltage profiles using differential evolution optimization method by Hammadi, Ahmed Sahib

“…The multi-objective function, which represents the summation of product five indices by corresponding weights, was utilized to identify the candidate buses to reduce the search space of the algorithm. …”
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Hyperdize Jaya Algorithm for Harmony Search Algorithm's Parameters Selection by Alaa A., Al-Omoush, Al-Sewari, Abdul Rahman Ahmed Mohammed, Ameen, Bahomaid, Alamri, Hammoudeh S., Kamal Z., Zamli

“…This paper present a successful method to tune the parameters of the harmony search algorithm, which is a well-known meta-heuristic algorithm. …”
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

“…Providing a balanced partitioning with equal weights are widely studied. However, in heterogeneous architecture, process heterogeneity demands partitions with different weights. …”
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Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization by Nur Iffah, Mohamed Azmi

“…This research aims to improve the PSO-PID tuning algorithms by integrating the tuning process with the Variable Weight Grey-Taguchi Design of Experiment (DOE) method. …”
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A Preliminary Study on Camera Auto Calibration Problem Using Bat Algorithm by Mohd Annuar, Khalil Azha, Selamat, Nur Asmiza, Jaafar, Hazriq Izzuan, Mohamad, Syahrul Hisham

“…This paper attempts to implement a stochastic optimization algorithm called Bat Algorithm in order to find optimal values of the intrinsic parameters. …”
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Master-leader-slave cuckoo search with parameter control for ANN optimization and its real-world application to water quality prediction by Jaddi N.S., Abdullah S., Malek M.A.

A study on the parameter selection of bat algorithm in in optimizing parameters in camera auto calibration problem by Mohd Said, Rahaini, A Aziz, Khairul Azha, Zainal Abidin, Amar Faiz, Mat Jizat, Jessnor Arif, Mohd Khairuddin, Ismail, Widiyanto, Sigit, Abdul Waduth, Mohamed Faisal

“…By studying the echolocation behavior of the microbats, the bats will try to improve the fitness with each iteration. The Bat Algorithm's performance is evaluated using a case study from a database from Le2i Universite de Bourgoune. …”
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Evaluating Bees Algorithm for Sequence-based T-way Testing Test Data Generation by M. H., Mohamed Zabil, Kamal Z., Zamli, K. C., Lim

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Using algorithmic taxonomy to evaluate lecture workload: a case study of services application prototype in the UPM KM Portal by Abdul Hamid, Jamaliah, Mohayidin, Mohd Ghazali, Selamat, Mohd Hasan, Ibrahim, Hamidah, Abdullah, Rusli, Hashim, Ruhil Hayati

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Multiobjective optimization using particle swarm optimization with non-Gaussian random generators by Ganesan, T., Vasant, P., Elamvazuthi, I.

“…In this work, a real-world MO problem (resin-bonded sand mould system) is tackled using Particle Swarm Optimization (PSO) in conjunction with the weighted-sum approach. Random generators (stochastic engines) provides sufficient randomness for the algorithm during the search process. …”
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