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Network reconfiguration and control for loss reduction using genetic algorithm by Jawad, Mohamed Hassan Izzaldeen

“…The proposed solution to this problem is based on a general combinatorial optimization algorithm known as Genetic Algorithm, and the load flow equations in distribution network. …”
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Loss reduction in distribution networks using new network reconfiguration algorithm by Kashem, M.A., Moghavvemi, M., Mohamed, A., Jasmon, G.B.

“…The first stage of this solution algorithm finds a loop which gives the maximum loss reduction in the network. …”
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Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic by Yap, Soon Teck

“…An integrated solution for the above problem is the ECQ Routing Algorithm. …”
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Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

“…Baldwinian learning uses learning algorithm to change the fitness landscape, but the solution that is found is not encoded back into genetic string. …”
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Decentralized traffic signal control for grid traffic network using genetic algorithm by Min Keng Tan, Helen Sin Ee Chuo, Kiam Beng Yeo, Renee Ka Yin Chin, Sha Huang, Kenneth Tze Kin Teo

“…Besides, the inherent deterministic behavior limits the algorithm to explore the solution space in searching for the optimum traffic solution. …”
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Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems by Ibrahim, Ashraf Osman, Shamsuddin, Siti Mariyam, Qasem, Sultan Noman

“…This paper presents a hybrid of the multiobjective evolutionary algorithm to gain a better accuracy of the fi nal solutions.The aim of using the hybrid algorithm is to improve the multiobjective evolutionary algorithm performance in terms of the enhancement of all the individuals in the population and increase the quality of the Pareto optimal solutions.The multiobjective evolutionary algorithm used in this study is a nondominated sorting genetic algorithm-II (NSGA-II) together with its hybrid, the backpropagation algorithm (BP), which is used as a local search algorithm to optimize the accuracy and complexity of the three-term backpropagation (TBP) network. …”
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Hybrid NSGA-II Optimization for Improving the Three-Term BP Network for Multiclass Classification Problems by Ibrahim, Ashraf Osman, Shamsuddin, Siti Mariyam, Qasem, Sultan Noman

“…The multiobjective evolutionary algorithm used in this study is a nondominated sorting genetic algorithm-II (NSGA-II) together with its hybrid, the backpropagation algorithm (BP), which is used as a local search algorithm to optimize the accuracy and complexity of the three-term backpropagation (TBP) network. …”
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Loss reduction in distribution networks by network reconfiguration: a two stage solution approach by Nallagownden, Perumal

“…The first stage of this solution algorithm finds a loop, which gives the maximum loss reduction in the network. …”
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A survey of state of the art: hierarchical routing algorithms for wireless sensor networks by Kareem, Husam, Hashim, Shaiful Jahari, Sali, Aduwati, Subramaniam, Shamala

“…Many researches have been done to solve this problem or at least find a solution to decrease the energy consumption. One of those solutions is using efficient routing algorithm. …”
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Improved cuckoo search based neural network learning algorithms for data classification by Abdullah, Abdullah

“…Specifically, 6 benchmark classification datasets are used for training the hybrid Artificial Neural Network algorithms. …”
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Fine-tuning approach in metaheuristic algorithm to prolong wireless sensor networks nodes lifetime by Rahiman, Amir Rizaan, Williams, Temitope Betty, Zakaria, Muhammad D.

“…A set of simulations has been performed using MATLAB R2018b on the proposed solution, namely the energy efficient of genetic (EEG) algorithm and has revealed that the solution outperforms the network lifetime and cluster head load of the existing solution.…”
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A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah by Salmah , Fattah

“…The algorithm introduces the fuzzy Pareto dominance concept to compare two solutions and uses the scalar decomposition method when one solution cannot dominate the other in terms of the fuzzy dominance level. …”
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A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks by Salmah Fattah

“…The algorithm introduces the fuzzy Pareto dominance concept to compare two solutions and uses the scalar decomposition method when one solution cannot dominate the other in terms of the fuzzy dominance level. …”
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Crosstalk-Free Scheduling Algorithms for Routing in Optical Multistage Interconnection Networks by Raja Mohd Auzar, Tengku Dian Shahida

“…Multistage Interconnection Networks (MINs) have been used in telecommunication networks for many years. …”
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A robust GA-based QoS routing algorithm for solving multi-constrained path problem by Yussof S., See O.H.

“…However, the actual link metrics in a QoS-aware network is dynamic and may continuously change over time and since the path given by the routing algorithm is computed using the state information available to the router, which may or may not be up-to-date, it is possible that a feasible path returned by the algorithm may turn out to be no longer valid. …”

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.

Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

“…Optimal power flow (OPF) solution is a crucial tool in electric power networks operation. …”
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Backpropagation neural network based on local search strategy and enhanced multi-objective evolutionary algorithm for breast cancer diagnosis by Ashraf Osman, Ibrahim, Siti Mariyam, Shamsuddin, Abdulrazak, Yahya Saleh, Ahmed, Ali, Mohd Arfian, Ismail, Shahreen, Kasim

“…However, the performance of such methods is based on the algorithms or technique. In this paper, we develop an intelligent technique using multiobjective evolutionary method hybrid with a local search approach to enhance the backpropagation neural network. …”
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Wavelet neural networks based solutions for elliptic partial differential equations with improved butterfly optimization algorithm training by Lee, Sen Tan, Zainuddin, Zarita, Ong, Pauline

“…Although the gradient information of the commonly used gradient descent training algorithm in WNNs may direct the search to optimal weight solutions that minimize the error function, the learning process is slow due to the complex calculation of the partial derivatives. …”
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BAT-BP: A new BAT based back-propagation algorithm for efficient data classification by Mohd. Nawi, Nazri, M. Z., Rehman, Hafifi, Nurfarian, Khan, Abdullah, Siming, Insaf Ali

“…This study intends to show the superiority (time performance and quality of solution) of the proposed meta-heuristic Bat-BP algorithm over other more standard neural network training algorithms. …”
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