Search Results - (( data optimization method algorithm ) OR ( a reflection method algorithm ))

A novel peak load shaving algorithm for isolated microgrid using hybrid PV-BESS system by Rana, M.M., Romlie, M.F., Abdullah, M.F., Uddin, M., Sarkar, M.R.

“…Peak shaving service can be found from this algorithm as a simple and forcible way. A comparative analysis has been conducted of the proposed algorithm with the conventional methods. …”
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Estimation of photovoltaic models using an enhanced Henry gas solubility optimization algorithm with first-order adaptive damping Berndt-Hall-Hall-Hausman method by Ramachandran, Murugan, Sundaram, Arunachalam, Ridha, Hussein Mohammed, Mirjalili, Seyedali

“…The existing literature extensively explores the utilization of powerful Metaheuristic Algorithms (MAs) to address the complex constrained optimization problem in PV systems and achieve optimal solutions. …”
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New learning algorithm based on Hidden Markov Model (HMM) as stochastic modelling for pattern calssification by Balakrishnan, Malarvili, Ting, Chee Ming, Shaikh Salleh, Sheikh Hussain

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Hybrid optimization approach to estimate random demand by Wahab, Musa, Ku-Mahamud, Ku Ruhana, Yasin, Azman

“…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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Classification of Diabetes Mellitus using Ensemble Algorithms by Noor, N.A.B.S., Elamvazuthi, I., Yahya, N.

“…Diabetes Mellitus (DM) is one of the most prevalent diseases in the world today which is associated by having high glucose levels in the body either due to inadequate production of insulin or the body cell's not responding towards the produced insulin. Data mining and machine learning techniques can be extremely useful in classification of DM considering the need to have a shift from current traditional methods which use sharp needles to draw blood towards a non - invasive method. …”
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

“…Any optimization algorithm is suitable for only a specific domain of optimization problems. …”
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Optimization Method Using Modified Harmony Search For Coverage And Energy Efficiency In Wireless Sensor Network by Halim, Nurul Hamimi

“…Coverage and energy efficiency metrics are two fundamental issues for almost all types of application in wireless sensor network (WSNs).Coverage reflects how well an area is monitored by sensor nodes and in energy efficient networks where less energy is consumed to provide the same level of services.These twin specifics are presented to evaluate the performance of a wireless sensor network.Due to its simplicity and ease of analysis,full coverage is widely implemented in many theoretical studies.However,sometimes full coverage is not the best way to represent some real-world application due to its strong restrictions and its deterministic characteristics.In this thesis,Modified Harmony Search algorithm (MHS) is proposed to achieve a sensor node deployment such that the covered area is optimal and data transfer has low energy consumption.Through computer simulations, experimental results verified that the proposed method improved the coverage of area in compare to some related methods.Based on the result obtain from every experiments,coverage area percentage performance is affected by the number of hotspots.This is shown by Harmony Search (HS) based method where the coverage area percentage increases as the number of hotspot increase. …”
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Optimizing LSTM S2S models with Evolutionary Mating Algorithm (EMA) for direct multi-step forecasting of household electrical power consumption by Al Mamun, Md Habib, Zuriani, Mustaffa, Junaida, Sulaiman, Mohd Herwan, Sulaiman

“…EMA successfully identifies optimal parameters, and EMA-optimized model achieved a significant improvement in accuracy over to baseline methods. …”
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Prediction of payment method in convenience stores using machine learning by Pratondo, Agus, Novianty, Astri, Pudjoatmodjo, Bambang

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Coverage and connectivity maximization for wireless sensor networks using improved chaotic grey wolf optimization by Shaikh, Muhammad Suhail, Wang, Chang, Xie, Senlin, Zheng, Gengzhong, Dong, Xiaoqing, Qiu, Shuwei, Mohd Ashraf, Ahmad, Raj, Saurav

“…The Grey Wolf Optimizer (GWO) is enhanced using a chaotic map, improving its ability to find the best solutions and achieve faster convergence, resulting in the ICGWO algorithm. …”
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Hydraulic characterization of PVC-O pipes by means of transient tests by Ghazali, M. F., Nizwan, Che Ku Eddy, Ismail, Nurazima, Sani, M. S.M., Yusof, Mohd Fadhlan M., Mohamed, Zamri

“…The data analysis of the signal that then to be decomposed into a series of wave composition with the use of EEMD signal masking method by using the matrix laboratory (MATLAB) software. …”
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Optimization-based method for estimating the transmission rate of COVID-19 during the lockdown in Malaysia by Alsayed, Abdallah, Aqel, Mohammad O. A., Kamil, Raja, Sadir, Hayder, Abuzaiter, Alaa, Alezabi, Kamal Ali, Sari, Hasan

“…The Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) were implemented to determine the daily transmission rate β(t) that fits the SIR model to the actual data. …”
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Block based low complexity iterative QR precoder structure for Massive MIMO by Mok, Li Suet

“…The results of the increase in the number of BS antennas with a fixed number of users, the proposed method achieved up to 20% and 60% compared to regular BD and ZF algorithms respectively. …”
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Design and development of intelligent 3d model recognition and inspection system in die stamping industry by Suryana, Nanna, Widodo, Wahyono Sapto, Hussin, Burairah, Mohd. Yusoh, Zeratul Izzah, Akbar, Habibullah

“…To overcome this problem, a new defect inspection algorithm for stamped part is developed and tested. …”
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Enhanced efficiency and stability photovoltaic systems integrating improved MPPT photovoltaic systems / Mohd Hazni Abdul Halim Shah by Abdul Halim Shah, Mohd Hazni

“…A methodical approach was employed, including an extensive literature review, system design, actual and simulated data simulations, and performance analysis. …”
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OPTIMIZATION-BASED METHOD FOR ESTIMATING THE TRANSMISSION RATE OF COVID-19 DURING THE LOCKDOWN IN MALAYSIA by Alsayed A., Aqel M.O.A., Kamil R., Sadir H., Abuzaiter A., Alezabi K.A., Sari H.

“…The Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) were implemented to determine the daily transmission rate ?…”

Sensitivity-based fuzzy multi-objective portfolio model with Value-at-Risk by Zhang, H., Watada, J., Wang, B.

“…Meanwhile, based on the fuzzy simulation technique, the model adapted to a series of different distributed fuzzy variable, an improved particle swarm optimization algorithm (IPSO) is used for numerical simulations. …”
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Asset liability management model: The case of selected Islamic banks in Malaysia / Chong Hui Ling by Chong , Hui Ling

“…This method produces a solution that minimises the gap between these objectives, targets and actual performance. …”
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A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio by Wang, B., Li, Y., Wang, S., Watada, J.

“…Then the proposed model is solved by a fuzzy simulation-based multi-objective particle swarm optimization algorithm, where the global best of each iteration is determined by an improved dominance times-based method. …”
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A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio by Wang, B., Li, Y., Wang, S., Watada, J.

“…Then the proposed model is solved by a fuzzy simulation-based multi-objective particle swarm optimization algorithm, where the global best of each iteration is determined by an improved dominance times-based method. …”
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