Search Results - intelligence model bat algorithm

Application of Bat Algorithm and Fuzzy Systems to Model Exergy Changes in a Gas Turbine by A.L., Tamiru, M. Hashim, Fakhruldin

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Bat algorithm and neural network for monthly streamflow prediction by Zaini N., Malek M.A., Yusoff M., Osmi S.F.C., Mardi N.H., Norhisham S.

“…Therefore, this study proposed on the development of streamflow prediction model AI techniques namely Bat algorithm (BA) and backpropagation neural network (BPNN). …”

Comparison of mabsa, PSO and GWO of PI-PD controller for dc motor by Nur Naajihah, Ab Rahman

“…The swarm intelligence group selected Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Modified Adaptive Bats Sonar Algorithms (MABSA) to optimize the parameters of the PI-PD controller. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

“…The firefly algorithm remains a feasible alternative for shallow architectural network models, while metaheuristic algorithms such as the Particle swarm algorithm and Bat algorithm are better options for deeper architectural network models. …”
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A Novel Hybrid Evolutionary Data-Intelligence Algorithm for Irrigation and Power Production Management: Application to Multi-Purpose Reservoir Systems by Yaseen, Zaher, Ehteram, Mohammad, Hossain, Md., Fai, Chow, Koting, Suhana, Mohd, Nuruol Syuhadaa, Jaafar, Wan Zurina Wan, Afan, Haitham Abdulmohsin, Lai, Sai Hin, Zaini, Nuratiah, Ahmed, Ali, El-Shafie, Ahmed

“…The current research is devoted to the implementation of hybrid novel meta-heuristic algorithms (e.g., the bat algorithm (BA) and particle swarm optimization (PSO) algorithm) to formulate multi-purpose systems for power production and irrigation supply. …”
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A novel hybrid evolutionary data-intelligence algorithm for irrigation and power production management: Application to multi-purpose reservoir systems by Yaseen Z.M., Ehteram M., Hossain M.S., Fai C.M., Koting S.B., Mohd N.S., Jaafar W.Z.B., Afan H.A., Hin L.S., Zaini N., Ahmed A.N., El-Shafie A.

Application of augmented bat algorithm with artificial neural network in forecasting river inflow of hydroelectric reservoir stations in Malaysia by Joe Wee Wei, Mr.

“…Despite there is only a limited number of simulation systems, existing methods failed to efficiently foresee the SF data and the methods are not cost-effective and takes a long time to carry out. Artificial intelligence (AI) was implemented to build forecasting models. …”

Investigation on the potential to integrate different artificial intelligence models with metaheuristic algorithms for improving river suspended sediment predictions by Ehteram M., Ghotbi S., Kisi O., Ahmed A.N., Hayder G., Fai C.M., Krishnan M., Afan H.A., EL-Shafie A.

Performance comparison of different swarm intelligence methods towards benchmark functions by Song, Wen Huan

“…Hence, the objective of this research is to analyse different Particle Swarm Optimization (PSO) models and to identify the best method in SI. The original version of PSO, Inertia Weight PSO (IWPSO), Linearly Decrease Inertia Weight PSO (LDIW-PSO), Random Inertia Weight PSO (RIW-PSO), Constriction Factor PSO (CF-PSO) along with and without velocity clamping (VC) are analyzed and compared with Grey Wolf Optimizer (GWO) and Bat Algorithm (BA). …”
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Optimizing the Social Force Model Using New Hybrid WOABAT-IFDO in Crowd Evacuation in Panic Situation by Hamizan, Sharbini, Roselina, Sallehuddin, Habibollah, Haron

“…Thus, this research proposes optimization using the one of the latest nature inspired algorithm namely WOABAT-IFDO (Whale-Bat and Improved Fitness-Dependent Optimization) in the SFM interaction component. …”
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A comprehensive overview of classical and modern route planning algorithms for self-driving mobile robots by Wan Daud, Wan Mohd Bukhari, Abu, Nur Syuhadah, Omar, Siti Nashayu, Sohaimeh, Shahirul Ashraf, Adli,, M. H.

“…Classical or traditional methods, such as Roadmaps (Visibility Graph and Voronoi Diagram), Potential Fields, and Cell Decomposition, and modern methodologies such as heuristic-based (Dijkstra Method, A* Algorithms, and D* Algorithms), metaheuristics algorithms (such as PSO, Bat Algorithm, ACO, and Genetic Algorithm), and neural systems such as fuzzy neural networks or fuzzy logic (FL) and Artificial Neural Networks (ANN) are described in this report. …”
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