Search Results - (( variable generation learning algorithm ) OR ( evolution optimisation system algorithm ))

Optimisation of Biochemical Systems Production using Hybrid of Newton Method, Differential Evolution Algorithm and Cooperative Coevolution Algorithm by Mohd Arfian, Ismail, Mezhuyev, Vitaliy, Kohbalan, Moorthy, Shahreen, Kasim, Ashraf Osman, Ibrahim

“…The proposed method is used to solve the optimisation problem in optimise the production of biochemical systems. …”
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Optimal placement, sizing and power factor of distributed generation: A comprehensive study spanning from the planning stage to the operation stage by Huy P.D., Ramachandaramurthy V.K., Yong J.Y., Tan K.M., Ekanayake J.B.

“…Electric power factor; Electric power transmission networks; Evolutionary algorithms; Optimization; Differential Evolution; Differential evolution algorithms; Distributed generation source; Multiple distributed generations; Optimal allocation; Optimisations; Power factorAbstract; Power system constraints; Distributed power generation; algorithm; distribution system; energy planning; operations technology; optimization…”

Performance evaluation and benchmarking of an extended computational model of ant colony system for DNA sequence design by Zuwairie, Ibrahim, Mohd Falfazli, Mat Jusof, Mohd Zaidi, Mohd Tumari

“…Ant colony system (ACS) algorithm is one of the biologically inspired algorithms that have been introduced to effectively solve a variety of combinatorial optimisation problems. …”
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Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China by Sattar Hanoon M., Najah Ahmed A., Razzaq A., Oudah A.Y., Alkhayyat A., Feng Huang Y., kumar P., El-Shafie A.

“…Machine learning models have been effectively applied to predict certain variable in several engineering applications where the variable is highly stochastic in nature and complex to identify utilizing the classical mathematical models. …”

Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods by Kadhem, Athraa Ali

“…This study sought to examine the performance of three newly proposed techniques, for reliability assessment of the power systems, namely Disparity Evolution Genetic Algorithm (DEGA), Binary Particle Swarm Optimisation (BPSO), and Differential Evolution Optimization Algorithm (DEOA). …”
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Dynamic Bayesian Networks and Variable Length Genetic Algorithm for Dialogue Act Recognition by Ali Yahya, Anwar

“…In the selection phase, a new variable length genetic algorithm is applied to select the lexical cues. …”
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Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance by Allawi, Mohammed Falah, Jaafar, Othman, Mohamad Hamzah, Firdaus, Koting, Suhana, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

“…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
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Comparison of Electricity Load Prediction Errors Between Long Short-Term Memory Architecture and Artificial Neural Network on Smart Meter Consumer by Salleh N.S.M., Suliman A., J�rgensen B.N.

Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition by Yahya, Anwar Ali, Mahmod, Ramlan, Ramli, Abd Rahman

“…The model is, essentially, a dynamic Bayesian network induced from manually annotated dialogue corpus via dynamic Bayesian machine learning algorithms. Furthermore, the dynamic Bayesian network's random variables are constituted from sets of lexical cues selected automatically by means of a variable length genetic algorithm, developed specifically for this purpose. …”
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Evaluating different machine learning models for predicting municipal solid waste generation: a case study of Malaysia by Latif S.D., Hazrin N.A.B., Younes M.K., Ahmed A.N., Elshafie A.

“…Therefore, one of the aims of this research was to investigate the use of machine learning algorithms and its benefits. The machine learning algorithms investigated are specifically Gaussian process regression (GPR), ensemble of trees and neural networks. …”

Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

“…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
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SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA by AHMED IZZELDIN, HUZAIFA TAWFEIG

“…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
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Multi-stage thermal-economical optimization of compact heat exchangers: A new evolutionary-based design approach for real-world problems by Yousefi M., Darus A.N., Yousefi M., Hooshyar D.

iBUST: An intelligent behavioural trust model for securing industrial cyber-physical systems by Azad, Saiful, Mahmud, Mufti, Kamal Zuhairi, Zamli, Kaiser, M. Shamim, Jahan, Sobhana, Razzaque, Md Abdur

“…In addition, a new optimisation model for finding optimum parameter values in the MEDF and an algorithm for transmuting a 1D quantitative feature into a respective categorical feature are developed to facilitate the model. …”
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An Optimal Scheduling Controller for Virtual Power Plant and Microgrid Integration Using the Binary Backtracking Search Algorithm by Abdolrasol M.G.M., Hannan M.A., Mohamed A., Amiruldin U.A.U., Abidin I.B.Z., Uddin M.N.

Enhancing wind power forecasting accuracy with hybrid deep learning and teaching-learning-based optimization by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

“…This paper presents an innovative approach that combines deep learning (DL) with Teaching-Learning-Based Optimization (TLBO) to predict wind power output accurately. …”
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A bayesian network approach to identify factors affecting learning of Additional Mathematics by Ong, Hong Choon, Kumarenthiran A/L Chandrasekaran

“…Constraint-based algorithms and score-based algorithms are used to generate the networks into several categories to compare and identify the strong relationships among the factors that affect the students’ learning of the subject. …”
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Short-Term forecasting of floating photovoltaic power generation using machine learning models by Mohd Herwan, Sulaiman, Mohd Shawal, Jadin, Zuriani, Mustaffa, Mohd Nurulakla, Mohd Azlan, Hamdan, Daniyal

“…The results indicate that the Neural Networks model consistently outperforms the other machine learning algorithms in terms of predictive accuracy. …”
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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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Gas Identi cation by Using a Cluster-k-Nearest-Neighbor by Brahim Belhaouari, samir

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