Search Results - (( based optimization means algorithm ) OR ( variable operations using algorithm ))

Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

“…Adopting the medoid instead of the mean can enhance the efficiency. However, the complexity of the kmedoid based algorithms in general is more than the complexity of the k-means based algorithms. …”
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Optimizing dam and reservoir operations using machine learning by Mohammad Abdullah Adib Almubaidin

Dynamic Economic Dispatch For Power System by Hussein, Saif Tahseen

“…Through an appropriate utilization of the structural features of the model, a solution algorithm based on Particle Swarm Optimization is developed. …”
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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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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

“…In order to validate the proposed algorithm, a number of experiments using various datasets were conducted and compared the outcomes with different�state-of-the-art algorithms. …”

Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

“…The effectiveness of the proposed LSA + LSTM model is assessed using battery aging data from the NASA dataset. In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”

Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems by Bashar AbedAl Mohdi Talal AlDeeb

“…The solution’s construction is modified using the concept of global best operator that is used in the Particle Swarm Optimization (PSO). …”

Streamflow prediction with large climate indices using several hybrid multilayer perceptrons and copula Bayesian model averaging by Panahi F., Ehteram M., Ahmed A.N., Huang Y.F., Mosavi A., El-Shafie A.

Profit Optimization of a Refrigerated Gas Plant by Yusoff, Nooryusmiza, Ramasamy , Marappagounder, Yusup, Suzana

“…To widen its profit margin, the plant needs to operate more efficiently. This requires continuous re-evaluation of the operating conditions through an efficient optimization algorithm. …”
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Profit Optimization of a Refrigerated Gas Plant by Yusoff, Nooryusmiza, Ramasamy , Marappagounder, Yusup, Suzana

“…To widen its profit margin, the plant needs to operate more efficiently. This requires continuous re-evaluation of the operating conditions through an efficient optimization algorithm. …”
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Profit Optimization of a Refrigerated Gas Plant by Yusoff, Nooryusmiza, Ramasamy , Marappagounder, Yusup, Suzana

“…To widen its profit margin, the plant needs to operate more efficiently. This requires continuous re-evaluation of the operating conditions through an efficient optimization algorithm. …”
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Prediction and multi-criteria-based schemes for seamless handover mechanism in mobile WiMAX networks by Mubarak, Mohammed Awadh Ahmed Ben

“…In the proposed HATSC scheme, the AHP method is uese for criteria weighting, while the TOPSIS method uses for the selection technique based on a multi-criteria decision-making algorithm is proposed. …”
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Hybrid dynamic scheduling model for flexible manufacturing system with machine availability and new job arrivals by Paslar, Shahla

“…The idea of hybridizing the newly developed biogeography based optimization algorithm (BBO) with variable neighborhood structure (VNS) is proposed in order to produce a high performance initial schedule in terms of minimum completion time, tardiness and flow time within reasonable amount of time. …”
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Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail by Sh. Ismail, Faridah

“…An intelligent predictive model will replace the lengthy procedures by predicting the properties using known fiberboard characteristics. Back-propagation algorithm is a training method widely used in a multilayer perceptron Neural Network model. …”
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Optimization of Microbial Electrolysis Cell for Sago Mill Wastewater Derived Biohydrogen via Modeling and Artificial Neural Network by Mohamad Afiq, Mohd Asrul

“…The model reliability describes the second sub-objective, which is to determine the feasible operating window of the MEC using multiple-objective optimization based on the nonlinear convex method using gradient descent algorithm as the objective function in maximizing the percentage efficiency of the MEC after validating the mathematical model. …”
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Conceptual Sim-Heuristic optimization algorithm to evaluate the climate impact on reservoir operations by Lai V., Huang Y.F., Koo C.H., Najah Ahmed A., El-Shafie A.

Modeling of Cu(II) adsorption from an aqueous solution using an Artificial Neural Network (ANN) by Khan T., Manan T.S.B., Isa M.H., Ghanim A.A.J., Beddu S., Jusoh H., Iqbal M.S., Ayele G.T., Jami M.S.

4E analysis of a two-stage refrigeration system through surrogate models based on response surface methods and hybrid grey wolf optimizer by Ahmed, R., Mahadzir, S., Mota-Babiloni, A., Al-Amin, M., Usmani, A.Y., Ashraf Rana, Z., Yassin, H., Shaik, S., Hussain, F.

“…However, traditional methods are based on a trial and error process to optimize these systems, and a global optimum operating point cannot be guaranteed. …”
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Vibration analysis for early detection of bearing failures by Gam, Kheng Shiang

“…Early detection of bearing failures using Predictive Maintenance (PdM) is critical for minimizing downtime and optimizing maintenance strategies. …”
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Modeling of Cu(II) adsorption from an aqueous solution using an Artificial Neural Network (ANN) by Khan, T., Manan, T.S.B., Isa, M.H., Ghanim, A.A.J., Beddu, S., Jusoh, H., Iqbal, M.S., Ayele, G.T., Jami, M.S.

“…The Fletcher-Reeves conjugate gradient backpropagation (BP) algorithm was the best fit among all of the tested algorithms (mean squared error (MSE) of 3.84 and R2 of 0.989). …”
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