Search Results - (( parameter optimization based algorithm ) OR ( partner selection method algorithm ))

Accuracy enhancement for zone mapping of a solar radiation forecasting based multi-objective model for better management of the generation of renewable energy by Ehteram M., Ahmed A.N., Fai C.M., Afan H.A., El-Shafie A.

Optimizing deep neuro-fuzzy classifier with a novel evolutionary arithmetic optimization algorithm by Talpur, N., Abdulkadir, S.J., Alhussian, H., Hasan, M.H., Abdullah, M.H.A.

“…But, the model faces two issues: (i) dataset with many features exponentially increases the fuzzy rule-base, (ii) parameters in the fuzzy rule-base are optimized using the gradient descent approach, which has the drawback of local minima. …”
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Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

“…In this paper, heuristic optimization approaches such as genetic algorithm and artificial bee colony are used to optimize the parameters of the antecedent part of interval type-2 fuzzy logic systems. …”
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Advances of metaheuristic algorithms in training neural networks for industrial applications by Chong H.Y., Yap H.J., Tan S.C., Yap K.S., Wong S.Y.

Dynamic smart grid communication parameters based cognitive radio network by Haider H.T., Muhsen D.H., Shahadi H.I., See O.H., Elmenreich W.

“…A differential evolution algorithm is used to select the optimal transmission parameters for given communication modes based on a fitness function that combines multiple objectives based on appropriate weights. …”

A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition by Koh J.S., Tan R.H.G., Lim W.H., Tan N.M.L.

“…Extensive studies prove the proposed algorithm outperforms bat algorithm (BA), improved grey wolf optimizer (IGWO), conventional PSO and P&O, with convergence time shorter than 0.3 s and tracking accuracy above 99% under different complex PSCs. � 2010-2012 IEEE.…”

Lithium-ion Battery State of Charge Estimation Method Using Optimized Deep Recurrent Neural Network Algorithm by Lipu M.S.H., Hannan M.A., Hussain A., Saad M.H.M., Ayob A., Muttaqi K.M.

Heuristic optimization-based wave kernel descriptor for deformable 3D shape matching and retrieval by Naffouti, S.E., Fougerolle, Y., Aouissaoui, I., Sakly, A., Mériaudeau, F.

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Heuristic optimization-based wave kernel descriptor for deformable 3D shape matching and retrieval by Naffouti, S.E., Fougerolle, Y., Aouissaoui, I., Sakly, A., Mériaudeau, F.

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Comprehensive power restoration approach using rule-based method for 11kV distribution network by Khalid A.R., Ahmad S.M.S., Shakil A., Pa N.N., Shafie R.M.

An Improved Grasshopper Optimization Algorithm Based Echo State Network for Predicting Faults in Airplane Engines by Bala, A., Ismail, I., Ibrahim, R., Sait, S.M., Oliva, D.

“…This problem is often formulated as a typical optimization problem. Metaheuristic algorithms are known to be excellent tools for solving optimization problems. …”
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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.

HABCSm: A Hamming Based t -way Strategy based on Hybrid Artificial Bee Colony for Variable Strength Test Sets Generation by Alazzawi, A.K., Rais, H.M., Basri, S., Alsariera, Y.A., Capretz, L.F., Imam, A.A., Balogun, A.O.

“…Consequently, a new meta-heuristic based t -way strategy called Hybrid Artificial Bee Colony (HABCSm) strategy, based on merging the advantages of the Artificial Bee Colony (ABC) algorithm with the advantages of a Particle Swarm Optimization (PSO) algorithm is proposed in this paper. …”
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HABCSm: A Hamming Based t -way Strategy based on Hybrid Artificial Bee Colony for Variable Strength Test Sets Generation by Alazzawi, A.K., Rais, H.M., Basri, S., Alsariera, Y.A., Capretz, L.F., Imam, A.A., Balogun, A.O.

“…Consequently, a new meta-heuristic based t -way strategy called Hybrid Artificial Bee Colony (HABCSm) strategy, based on merging the advantages of the Artificial Bee Colony (ABC) algorithm with the advantages of a Particle Swarm Optimization (PSO) algorithm is proposed in this paper. …”
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Enhancement and assessment of WKS variance parameter for intelligent 3D shape recognition and matching based on MPSO by Naffouti, S.E., Aouissaoui, I., Fougerolle, Y., Sakly, A., Meriaudeau, F.

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Modeling and Analysis of New Hybrid Clustering Technique for Vehicular Ad Hoc Network by Abdulrazzak H.N., Hock G.C., Mohamed Radzi N.A., Tan N.M.L., Kwong C.F.

“…Secondly, the K-value-calculating algorithm computes the optimal number of clusters. …”

Obso based fractional pid for mppt-pitch control of wind turbine systems by Mehedi, I.M., Al-Saggaf, U.M., Vellingiri, M.T., Milyani, A.H., Saad, N.B., Yahaya, N.Z.B.

“…The proposed model aims to effectually extract the maximum power point (MPPT) in the low range of weather conditions and save the WT in high wind regions by the use of pitch control. The OBSO algorithm is derived from the integration of oppositional based learning (OBL) concept with the traditional BSO algorithm in order to improve the convergence rate, which is then applied to effectively choose the parameters involved in the FOPID controller. …”
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Uncertainty parameters of battery energy storage integrated grid and their modeling approaches: A review and future research directions by Reza M.S., Hannan M.A., Ker P.J., Mansor M., Lipu M.S.H., Hossain M.J., Mahlia T.M.I.

Artificial Bee Colony for Minimizing the Energy Consumption in Mobile Ad Hoc Network by Tareq, M., Abed, S.A., Sundararajan, E.A.

“…The aim of this paper is to find the best possible route from the source to the destination based on a method inspired by the searching behaviour of bee colonies, i.e. artificial bee colony (ABC) algorithm. …”
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Application of Machine Learning and Deep Learning Algorithms for Landslide Susceptibility Assessment in Landslide Prone Himalayan Region by Bhattacharya S., Ali T., Chakravortti S., Pal T., Majee B.K., Mondal A., Pande C.B., Bilal M., Rahman M.T., Chakrabortty R.

“…We carefully selected relevant metrics based on existing research and conducted a multicollinearity analysis on each parameter to ensure the model?…”