Search Results - (( data optimization method algorithm ) OR ( data reflection model algorithm ))
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A novel peak load shaving algorithm for isolated microgrid using hybrid PV-BESS system
Published 2021“…To evaluate the effectiveness of the algorithm, simulation case studies have been conducted with actual load data and actual PV generation data. …”
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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
Published 2024“…The proposed EHGSO methodology based on the adaptive damping BHHH technique (EHGSOAdBHHH) is tested on Single Diode (SD), and Double Diode (DD) PV models using actual experimental data. EHGSOAdBHHH exhibits outstanding accordance with attained experimental data compared with other algorithms, and its superiority is validated using several statistical criteria.…”
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Hybrid optimization approach to estimate random demand
Published 2012“…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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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…Any optimization algorithm is suitable for only a specific domain of optimization problems. …”
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Classification of Diabetes Mellitus using Ensemble Algorithms
Published 2021“…Proposed DM classification model is chosen based on an optimized model reflected by their accuracy and performance of the model. …”
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Optimizing LSTM S2S models with Evolutionary Mating Algorithm (EMA) for direct multi-step forecasting of household electrical power consumption
Published 2026“…This study proposes a hybrid approach that combines a Long Short-Term Memory Sequence to Sequence (LSTM S2S) model with the Evolutionary Mating Algorithm (EMA) to optimize the model settings. …”
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Sensitivity-based fuzzy multi-objective portfolio model with Value-at-Risk
Published 2019“…In addition, compared with the VaR-FMOPSM model, our sensitivity-based improved model with the IPSO algorithm also performs better than Genetic Algorithm and Simulate Anneal Algorithm (SA), it provides the same performance on this point. …”
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Prediction of payment method in convenience stores using machine learning
Published 2023“…The Random Forest algorithm was employed due to its robustness in handling complex, high-dimensional data, and its ability to provide reliable predictions. …”
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Coverage and connectivity maximization for wireless sensor networks using improved chaotic grey wolf optimization
Published 2025“…A mathematical model for the WSN coverage and connectivity optimization problem is developed as the foundation. …”
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Design and development of intelligent 3d model recognition and inspection system in die stamping industry
Published 2012“…To overcome this problem, cost-effective appearance-based method is proposed to replace traditional method which based on model of object. …”
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Optimization-based method for estimating the transmission rate of COVID-19 during the lockdown in Malaysia
Published 2022“…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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Asset liability management model: The case of selected Islamic banks in Malaysia / Chong Hui Ling
Published 2017“…The study takes Bank Islam Malaysia Berhad‟s (BIMB) financial data to validate the model. The multi-faceted objectives consist of the bank‟s expected returns and risks tolerance with constraints (also known as restraining functions to reflect the limitations placed on the Islamic bank‟s operating requirements), established using computational mathematics and algorithms with the aid of the MATLAB programming software. …”
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A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio
Published 2018“…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
Published 2018“…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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Locating Optimum Receiver Position in Seismic Acquisition: Example from Carbonate Region
Published 2017“…In previous years, several methods have been studied and applied in order to improve the subsurface data by restoring true reflectivity, with certain degrees of success. …”
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OPTIMIZATION-BASED METHOD FOR ESTIMATING THE TRANSMISSION RATE OF COVID-19 DURING THE LOCKDOWN IN MALAYSIA
Published 2023“…The well-known Susceptible-Infected-Removed (SIR) epidemiological model was fitted to the actual data of infected cases from the official press to closely reflect the observed COVID-19 outbreak in Malaysia. …”
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Determining malaria risk factors in Abuja, Nigeria using various statistical approaches
Published 2018“…The optimal model based on the parsimony principles was obtained from the hill climbing algorithm with score metrics. …”
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Block based low complexity iterative QR precoder structure for Massive MIMO
Published 2021“…Besides, it has achieved up to 60% and 65% respectively for a fixed number of 128 and 512 BS antennas compared to ZF algorithm. 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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State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model
Published 2023“…In the first stage, the model is pre-trained using unlabeled data with unsupervised learning. …”
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