Search Results - (( using self method algorithm ) OR ( using optimization model algorithm ))

Improving the Muskingum flood routing method using a hybrid of particle swarm optimization and bat algorithm by Ehteram M., Othman F.B., Yaseen Z.M., Afan H.A., Allawi M.F., Malek M.B.A., Ahmed A.N., Shahid S., Singh V.P., El-Shafie A.

Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem by Anniza, Hamdan, San Nah, Sze, Say Leng, Goh, Kang Leng, Chiew, Wei King, Tiong

“…Hybridization in evolutionary algorithm mechanisms such as initialization methods, local searches, specific design operators, and self-adaptive parameters enhance the algorithm’s performance. …”
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Improving the Muskingum flood routing method using a hybrid of particle swarm optimization and bat algorithm by Ehteram, Mohammad, Othman, Faridah, Yaseen, Zaher Mundher, Afan, Haitham Abdulmohsin, Allawi, Mohammed Falah, Malek, Marlinda Abdul, Ahmed, Ali Najah, Shahid, Shamsuddin, Singh, Vijay P., El-Shafie, Ahmed

“…In this context, an optimization process that self-searches for the optimal values of these four parameters might improve the traditional Muskingum model. …”
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Malaysian menu planning model using Self-adaptive Hybrid Genetic Algorithm (SHGA) by Mohd Razali, Siti Noor Asyikin, Engku Abu Bakar, Engku Muhammad Nazri, Ku-Mahamud, Ku Ruhana, Arbin, Norazman, Rusiman, Mohd Saifullah

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Utilizing self-organization systems for modeling and managing risk based on maintenance and repair in petrochemical industries by Jaderi, Fereshteh, Ibrahim, Zelina Zaiton, Nikoo, Mehdi, Nikoo, Mohammad

“…For this purpose, operation impact, operation flexibility, maintenance cost, impact of safety and environment and frequency parameters had been considered as input; and using this model, the risk level is calculated. Utilizing genetic algorithms, the structures of all self-organizing systems are optimized. …”
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Lithium-ion Battery State of Charge Estimation Method Using Optimized Deep Recurrent Neural Network Algorithm by Lipu M.S.H., Hannan M.A., Hussain A., Saad M.H.M., Ayob A., Muttaqi K.M.

Malaysian menu planning model using Self-Adaptive Hybrid Genetic Algorithm (SHGA) by Mohd Razali, Siti Noor Asyikin, Engku Abu Bakar, Engku Muhammad Nazri, Ku Mahamud, Ku Ruhana, Arbin, Norazman, Rusiman, Mohd Saifullah

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Menu Planning Model for Malaysian Boarding School Using Self-Adaptive Hybrid Genetic Algorithms by Siti Noor Asyikin, Mohd Razali

“…Hybridization technique of local search method and self-adaptive strategy have improved the performance of traditional genetic algorithm through balanced exploitation and exploration scheme. …”
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Two-stage feature selection using ranking self-adaptive differential evolution algorithm for recognition of acceleration activity by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md. Nasir, Mustapha, Norwati, Perumal, Thinagaran, Mohamed, Raihani

“…The proposed algorithm is capable of selecting the optimal feature subsets while improving the recognition of acceleration activity using a minimum number of features. …”
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Nature-Inspired Drone Swarming for Wildfires Suppression Considering Distributed Fire Spots and Energy Consumption by Alsammak I.L.H., Mahmoud M.A., Gunasekaran S.S., Ahmed A.N., Alkilabi M.

“…Our quantitative tests show that the improved model has the best coverage (95.3%, 84.3% and 65.8%, respectively) compared to two other methods Levy Flight (LF) algorithm and Particle Swarm Optimization (PSO), which use the same initial parameter values. …”

Self-Adaptive Autoreclosing Scheme usingI Artificial Neural Network and Taguchi's Methodology in Extra High Voltage Transmission Systems by Desta, Zahlay Fitiwi

“…In addition, Taguchi's methodology is employed in optimizing the parameters of each algorithm used for training, and in deciding the number of hidden neurons of the neural network. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…However, the learning complexity of classification is increased due to the expansion number of learning model. Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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An intelligent framework for modelling and active vibration control of flexible structures by Mohd. Hashim, Siti Zaiton

“…The first controller design is formulated so as to allow on-line modeling, controller design and implementation and thus, yield a self-tuning control algorithm. …”
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Crossover and mutation operators of real coded genetic algorithms for global optimization problems by Lim, Siew Mooi

“…The rationale behind developing algorithms using real encoding of chromosome representations is the limitations of binary encoding. …”
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Deep continual learning for predicting blast-induced overbreak in tunnel construction / He Biao by He , Biao

“…Third, the overbreak prediction model is further integrated with metaheuristic algorithms, aiming to identify the optimal blasting parameters that can minimize overbreak. …”
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An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA by Bian, Hui

“…Using the NSL-KDD dataset for evaluation, the proposed method demonstrates superior performance compared to conventional algorithms and related deep learning techniques, achieving higher precision, recall, F1 scores and overall accuracy in both binary and multi-class classification tasks. …”
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

Artificial Neural Network Algorithms to Predict the Compressive Strength of Fly Ash-Based Geopolymers by Siaw Hui, Teo

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Earth observation micro-satellite design optimization using satellite simulator / Robertus Heru Triharjanto … [et al.] by Heru Triharjanto, Robertus

“…It is also find that due to full acces level, the self-made simulator as used in the research has good potential to be used in the optimization case with search algorithm.…”
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Nonlinear dynamic system identification and control via self-regulating modular neural network by Kiong, L.C., Rajeswari, M., Rao, M.V.C.

“…The proposed network is devised to overcome the redundancy problems of Gaussian neural networks that use square mesh partition method. In the SGMN, the problem space is decomposed into overlapping regions by expertise domain and the local expert models are graded according to their expertise level. …”
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