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

Neural network approach for global solar irradiance prediction at extremely short-time-intervals using particle swarm optimization algorithm by Aljanad A., Tan N.M.L., Agelidis V.G., Shareef H.

Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm by Farzin, Saeed, Singh, Vijay, Karami, Hojat, Farahani, Nazanin, Ehteram, Mohammad, Kisi, Ozgur, Allawi, Mohammed Falah, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

“…Design of hydraulic structures, flood warning systems, evacuation measures, and traffic management require river flood routing. A common hydrologic method of flood routing is the Muskingum method. The present study attempted to develop a three-parameter Muskingum model considering lateral flow for flood routing, coupling with a new optimization algorithm namely, Improved Bat Algorithm (IBA). …”
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The application of queuing theory model using the DSW Algorithm and the L-R Method to optimize customer flow at Pizza Hut / Anis Natasha Mohamad Nizam, Nurfatihah Nadirah Noor Azlan and Nur Izzati Aliah Fazli by Mohamad Nizam, Anis Natasha, Noor Azlan, Nurfatihah Nadirah, Fazli, Nur Izzati Aliah

“…One of the approximate methods that employs intervals at various a -cuts is the DSW Algorithm. …”
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Optimizing optimal path trace back for Smith-Waterman algorithm using structural modelling technique by Saliman, Nur Farah Ain

“…The optimizing of optimal path trace back system for Smith-Waterman algorithm using structural modelling techniques are presented in this paper. …”
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Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari by Mohammed , Heydari

“…An improved particle swarm algorithm (HPSOGA) is used to solve complex problems of water resources optimization. …”
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Power production optimization of model-free wind farm using smoothed functional algorithm by R., Mok, M. A., Ahmad

“…Whereby, the SFA based method is used to optimize the control parameter of each wind turbine such that the total power production of wind farm is maximized. …”
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3D virtual modelling and stabilization control of triple links inverted pendulum on two-wheeled system using enhanced interval type-2 fuzzy logic control by Muhammad Firdaus, Masrom

“…Two optimization algorithms are presented in this work which are Spiral Dynamic Algorithm (SDA) and Particle Swarm Optimization (PSO). …”
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Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions by Abbas, Iraq Tareq

“…In addition, the simulation random data for were used to solve single and bi-objective optimization PP and Sch.P to improve the validation and verify the performance of the proposed algorithms. …”
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Characteristic wavelength optimization for partial least squares regression using improved flower pollination algorithm by Pauline Ong, Pauline Ong, Jinbao Jian, Jinbao Jian, Jianghua Yin, Jianghua Yin, Guodong Ma, Guodong Ma

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Thin Film Roughness Optimization In The Tin Coatings Using Genetic Algorithms by Fauzi, Nur Faiqah, Mohamad Jaya, Abdul Syukor, Mohammad Jarrah, Mu’ath Ibrahim, Akbar, Habibullah

“…In order to represent the process variables and coating roughness, a quadratic polynomial model equation was developed. Genetic algorithms were used in the optimization work of the coating process to optimize the coating roughness parameters. …”
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Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun by Chong , Kai Lun

“…The proposed approach can be furthered categorized into two distinct stages: forecasting modeling and optimization modeling. Artificial neural network (ANN) has been widely used in forecasting tasks. …”
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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.

“…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. …”

Gravitational Search Algorithm based Long Short-term Memory Deep Neural Network for Battery Capacity and Remaining Useful Life Prediction with Uncertainty by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Tiong S.K., Hossain M.J.

“…The RUL prediction uncertainty with a 95% confidence interval (CI) is also analyzed. The GSA algorithm optimizes the hyperparameters of the LSTM network to construct an optimal model. …”

A hybrid ANN for output power prediction and online monitoring in grid-connected photovoltaic system / Puteri Nor Ashikin Megat Yunus by Megat Yunus, Puteri Nor Ashikin

“…At this stage, the hybrid EPDEA was selected to be used in the system as it was the best optimization in the hybridization method. …”
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Modeling And Optimization Of Physical Vapour Deposition Coating Process Parameters For Tin Grain Size Using Combined Genetic Algorithms With Response Surface Methodology by Mohamad Jaya, Abdul Syukor, Muhamad, Mohd Razali, Abd Rahman, Md Nizam, Mohammad Jarrah, Mu'ath Ibrahim, Hasan Basari, Abd Samad

“…Additionally,analysis of variance(ANOVA) was used to determine the significant factors influencing resultant TiN coating grain size.Based on that,a quadratic polynomial model equation was developed to represent the process variables and coating grain size.Then,in order to optimize the coating process parameters, genetic algorithms (GAs) were combined with the RSM quadratic model and used for optimization work.Finally,the models were validated using actual testing data to measure model performances in terms of residual error and prediction interval (PI).The result indicated that for RSM,the actual coating grain size of validation runs data fell within the 95% (PI) and the residual errors were less than 10 nm with very low values, the prediction accuracy of the model is 96.09%.In terms of optimization and reduction the experimental data,GAs could get the best lowest value for grain size then RSM with reduction ratio of ≈6%, ≈5%, respectively.…”
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Multi-objectives process optimization in end milling process of aluminium alloy 6061-T6 using genetic algorithm by W., Safiei, Rahman, M. M., M.Y., Ali

“…The optimization process parameters of end milling were obtained using response surface methodology, mathematical models and the MOGA-II approach. …”
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Battery management optimization and lifecycle impact analysis for microgrid operation with V2G implementation / Muhammad Sufyan by Muhammad , Sufyan

“…The proposed energy management approach is solved using firefly algorithm, artificial bee colony, harmony search algorithm and particle swarm optimization. …”
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A matrix approach for minimum spanning tree in neutrosophic and application in medical waste management / Nur Haifa Ahmad Hayazim, Siti Nurain Zulkifli and Siti Nurhidayah Yaacob by Ahmad Hayazim, Nur Haifa, Zulkifli, Siti Nurain, Yaacob, Siti Nurhidayah

“…As a final step, a comparative study such as interval-valued neutrosophic minimum spanning tree (IVN-MST), interval-valued intuitionistic fuzzy minimum spanning tree (IVIF-MST) and interval-valued fuzzy minimum spanning tree (IVE-MST) is presented to point out the advantages of the proposed method over that of other existing algorithms. …”
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Optimization and prediction of battery electric vehicle driving range using adaptive fuzzy technique by Abulifa, Abdulhadi Abdulsalam

“…The study also developed an algorithm for predictive EMS using fuzzy model predictive control technique based on regression algorithm. …”
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Cutpoint determination methods in competing risks subdistribution model by Noor Akma Ibrahim, Abdul Kudus, Isa Daud, Mohd. Rizam Abu Bakar

“…Simulation results show that the deviance method has the desired properties. Permutation test is used to assess the level of significance and bootstrap confidence interval is obtained for the optimal cutpoint. …”
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