Search Results - (( data optimization method algorithm ) OR ( a distribution function algorithm ))

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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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.

Optimal demand response of solar energy generation using Genetic Algorithm / Muhammad Asyraaf Adlan by Adlan, Muhammad Asyraaf

“…The objective function of the algorithm minimizes the daily losses due to load shedding while ensuring a balanced and stable energy distribution to the end users. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

“…The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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Space allocation for examination scheduling using Genetic Algorithm / Alya Kauthar Azman by Azman, Alya Kauthar

“…This study applies Genetic Algorithms (GA) to optimize space distribution for test scheduling, addressing the challenge of managing multiple test sessions across distinct locations. …”
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Sizing and placement of solar photovoltaic plants by using time-series historical weather data by Ali, A., Mohd Nor, N., Ibrahim, T., Fakhizan Romlie, M.

“…The total energy loss index was formulated as the main objective function, and the optimization problem was solved by mixed integer optimization by using genetic algorithm. …”
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Sizing and placement of solar photovoltaic plants by using time-series historical weather data by Ali, A., Mohd Nor, N., Ibrahim, T., Fakhizan Romlie, M.

“…The total energy loss index was formulated as the main objective function, and the optimization problem was solved by mixed integer optimization by using genetic algorithm. …”
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Optimal Power Flow of power systems using Harris Hawks Optimization and Salp Swarm Algorithm by Zohrul, Islam Mohammad

“…The obtained results showed the decent improvement comparing to other swarm-based techniques like Whale Optimization Algorithm (WOA), Math Flame (MF), and Glowworm Optimization Algorithm (GOA) in terms of convergence performance and quality. …”
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Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH by Norhafidzah, Mohd Saad

“…A hybrid population – based stochastic optimization method named MVMO-SH algorithm is proposed to optimize PVDG locations and sizes in the grid system network. …”
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Metaheuristic optimization techniques for localization in outdoor wireless sensor networks: a comprehensive review by Gumaida, Bassam, Ibrahim, Adamu Abubakar

“…This paper provides an overview of localization algorithms, including centralized and distributed algorithms. …”
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A new variant of black hole algorithm based on multi population and levy flight for clustering problem by Haneen Abdul Wahab, Abdul Raheem

“…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems. …”
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Distributed joint power control, beamforming and spectrum leasing for cognitive two-way relay networks by Iranpanah, Havzhin

“…A search method with numerous advantages over conventional algorithms, has been designed to solve the optimization problems with an enhanced global optimality and convergence speed. …”
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

“…Any optimization algorithm is suitable for only a specific domain of optimization problems. …”
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New learning algorithm based on Hidden Markov Model (HMM) as stochastic modelling for pattern calssification by Balakrishnan, Malarvili, Ting, Chee Ming, Shaikh Salleh, Sheikh Hussain

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Controller placement problem in the optimization of 5G based SDN and NFV architecture by Ibrahim, Abeer Abdalla Zakaria

“…A heuristic called dynamic mapping and multi-stage CPP algorithm (DMMCPP) was developed to solve CPP as resource allocation in a distributed 5G-SDN-NFV-based network. …”
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Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

“…Lastly, in order to externally judge the validity of these types of clustering algorithms, there is a need for a method to correctly and efficiently evaluate their variant multiclass clustering results. …”
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Empowering Energy-Sustainable IoT Devices With Harvest Energy-Optimized Deep Neural Networks by Alzahrani, Saeed, Salh, Adeb, Audah, Lukman, A. Alhartomi, Mohammed, Alotaibi, Abdulaziz, Alsulami, Ruwaybih

“…A novel training was proposed for Deep Neural Network (DNN) algorithms chain rules to minimize the loss function based on updating the parameters of the weights hidden layer and convergence training to achieve near-optimal performance and minimize unneeded label data. …”
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Heuristic resource allocation algorithm for controller placement in multi-control 5G based on SDN/NFV architecture by Ibrahim, Abeer Abdalla Zakaria, Hashim, Fazirulhisyam, Noordin, Nor Kamariah, Sali, Aduwati, Navaie, Keivan, Fadul, Saber Mohammed Elnour

“…A Greedy Randomized Search (GRS) algorithm was used to solve the dynamic assignment of nodes to controllers to achieve load balancing. …”
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Optimal placement and sizing of renewable distributed generations and capacitor banks into radial distribution systems by Mahesh, K., Nallagownden, P., Elamvazuthi, I.

“…First a set of non-dominated Pareto-front data are called from the algorithm. …”
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Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli by Ahmad Kamaruddin, Saadi, Md. Ghani, Nor Azura, Mohamed Ramli, Norazan

“…The direct idea of making the conventional neural network learning algorithm more powerful towards outlying data is by replacing the mean square error (MSE) with a different symmetric and continuous cost function. …”
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