Search Results - (( using evolutionary tool algorithm ) OR ( using optimization method algorithm ))

Intelligent energy systems using the barnacles mating optimizer and evolutionary mating algorithm: Foundations, methods, and applications by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

“…Intelligent Energy Systems using the Barnacles Mating Optimizer and Evolutionary Mating Algorithm: Foundations, Methods, and Applications reveals the potential of innovative optimization algorithms to support sustainability in modern energy systems. …”
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Impact of evolutionary algorithm on optimization of nonconventional machining process parameters by B V, Raghavendra, R Annigiri, Anandkumar, Srikatamurthy, JS

“…Using a Python environment, three evolutionary algorithms such as, Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Firefly Algorithm (FA), were simulated to evaluate their effectiveness in minimizing surface roughness (Ra). …”
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Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms by Ridha, Hussein Mohammed

“…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
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Optimal demand response of solar energy generation using Genetic Algorithm / Muhammad Asyraaf Adlan by Adlan, Muhammad Asyraaf

“…The aim of this study is to optimize the demand response of solar energy generation using Genetic Algorithm (GA) to minimize the daily yield loss caused by load shedding. …”
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Multi-objective optimization of stand-alone hybrid renewable energy system by genetic algorithm by Nejad, Mohsen Fadaee

“…HOGA, as a new effective tool for multi-objective optimization by evolutionary algorithm is used in this research. …”
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An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming by Mohamad Ridzuan, Mohamad Radzi

“…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 comprehensive comparison of recent developed meta-heuristic algorithms for streamflow time series forecasting problem by Ahmed A.N., Van Lam T., Hung N.D., Van Thieu N., Kisi O., El-Shafie A.

Electricity distribution network for low and medium voltages based on evolutionary approach optimization by Hasan, Ihsan Jabbar

“…The PSO method has been used to solve the DG placement and sizing on the IEEE 34 and 123 nodes test systems, respectively. …”
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A high-performance democratic political algorithm for solving multi-objective optimal power flow problem by Ahmadipour M., Ali Z., Othman M.M., Bo R., Javadi M.S., Ridha H.M., Alrifaey M.

“…Simulation results are analyzed and compared with two popular and commonly used multi-objective-evolutionary algorithms namely, non-dominated sorting genetic algorithm II (NSGA-II) and the multi-objective particle swarm optimization (MOPSO) on the problem. …”

A high-performance democratic political algorithm for solving multi-objective optimal power flow problem by Ahmadipour, Masoud, Ali, Zaipatimah, Othman, Muhammad Murtadha, Bo, Rui, Javadi, Mohammad Sadegh, Ridha, Hussein Mohammed, Alrifaey, Moath

“…Simulation results are analyzed and compared with two popular and commonly used multi-objective-evolutionary algorithms namely, non-dominated sorting genetic algorithm II (NSGA-II) and the multi-objective particle swarm optimization (MOPSO) on the problem. …”
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Multi-Objective PSO with Passive Congregation for Load Balancing Problem by Marufuzzaman M., Timu M.A., Sarkar J., Islam A., Rahman L.F., Sidek L.M.

“…Efficient load balancing can minimize the simulation time of HLA and this optimization can be done using the multi-objective evolutionary algorithms (MOEA). …”

Early explorations of EEG as a method for interactive evolutionary design of 3-dimensional objects by Chew, Lin Hou, James Mountstephens, Teo, Jason Tze Wi

“…This paper introduces an automatic method for generation of 3D artforms using electroencephalogram (EEG). …”
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Predicting Petroleum Reservoir Properties from Downhole Sensor Data using an Ensemble Model of Neural Networks by Fatai Adesina, Anifowose, Jane, Labadin, Abdulazeez, Abdulraheem

“…One of such is the difficulty in determining the most suitable learning algorithm for optimal model performance. To save the cost, effort and time involved in the use of trial-and-error and evolutionary methods, this paper presents an ensemble model of ANN that combines the diverse performances of seven "weak" learning algorithms to evolve an ensemble solution in the prediction of porosity and permeability of petroleum reservoirs. …”
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Firefly algorithm-based neural network for GCPV system output prediction / Nor Syakila Mohd Zainol Abidin by Mohd Zainol Abidin, Nor Syakila

“…In the proposed MLFNN, FA was employed as the optimizer and search tools of the MLFNN training parameters. …”
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

“…These steps have conducted using the MEMPHA model and ROA algorithm to optimize three metrics: execution time, total communication volume, and imbalance ratio (load balancing). …”
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Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model by Yaseen, Z.M., Ebtehaj, I., Bonakdari, H., Deo, R.C., Danandeh Mehr, A., Mohtar, W.H.M.W., Diop, L., El-Shafie, A., Singh, V.P.

“…The proposed method is a novel combination of the ANFIS model with the firefly algorithm as an optimizer tool to construct a hybrid ANFIS-FFA model. …”
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Computational methods for self-assembly of DNA nanostructures / Ong Hui San by Ong, Hui San

“…Several approaches have been adopted including development of an autonomous tool that incorporated evolutionary optimization algorithm in constructing these heterogeneous DNA shapes and the application of heuristic through undirected graph theory as an annotation schema to produce the connectivity maps. …”
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Mobile game application development using evolutionary algorithms by Ong, Jia Hui

“…Evolutionary Programming (EP) is used as the main evolutionary technique in this study. …”
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Evolutionary genetic algorithm as a generative tools in identifying Malay, Chinese and Indian cultural product DNA / Izzuddinazwan Misri by Misri, Izzuddinazwan

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Enhancing benchmark optimization with evolutionary random approach: A comparative analysis of modified adaptive bats sonar algorithm (MABSA) by Nor Shuhada, Ibrahim, Nafrizuan, Mat Yahya, Saiful Bahri, Mohamed, Mohd Ismail, Yusof

“…Recently, evolutionary algorithms have emerged as powerful tools for solving complex optimization problems across various domains. …”
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