Search Results - (( re evaluation ((case algorithm) OR (_ algorithm)) ) OR ( panel simulation based algorithm ))
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Optimization Of Fuzzy Logic Controllers With Genetic Algorithm For Two-Part-Type And Re-Entrant Production Systems
Published 2008“…GDF and GSF controllers are evaluated for two test cases namely “two-part-type production line” and “re-entrant production system”. …”
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Sustainable renewable energy resources utilization in rural areas
Published 2016“…Results obtained from the transportation model have been validated based on other RE studies in the area. For the similar case study considered, it is noted that the minimized total cost obtained using transportation algorithm depicts an improvement in cost over integrated renewable energy system (IRES) models. …”
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Sustainable renewable energy resources utilization in rural areas
Published 2016“…Results obtained from the transportation model have been validated based on other RE studies in the area. For the similar case study considered, it is noted that the minimized total cost obtained using transportation algorithm depicts an improvement in cost over integrated renewable energy system (IRES) models. …”
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4
Software regression test case prioritization for object-oriented programs using genetic algorithm with reduced-fitness severity
Published 2015“…This paper propose an optimized regression test case selection and prioritization for object-oriented software based on dependence graph model analysis of the source code and optimized the selected test case using Genetic Algorithm. …”
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A regression test case selection and prioritization for object-oriented programs using dependency graph and genetic algorithm
Published 2014“…This paper presents an evolutionary regression test case prioritization for object-oriented software based on dependence graph model analysis of the affected program using Genetic Algorithm. …”
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Development of an augmented reality based facility layout planning and optimization / Tan Chee Hau
Published 2020“…Four cases studies have investigated this research whereby case study-1 is to evaluate the most suitable position and orientation of a new machine to be placed in an existing production floor, case study-2 is to maximize the area given and further maximize the productivity by optimizing the production sequence, case study-3 is about identifying the best position of a shared facility whereas the case study-4 identified the most effective production sequence in a robotic conveyor cell. …”
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7
Deep learning in public health: Comparative predictive models for COVID-19 case forecasting
Published 2024“…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”
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Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling
Published 2022“…The experimentations of the proposed algorithm are conducted using existing benchmark instances and a published case study on an energy-efficient job-shop model. …”
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9
Investigation of maximum power point tracking (MPPT) for active cooling mono-crystalline photovoltaic panel using fuzzy logic controller
Published 2017“…This system is develop in both simulation and experimental. A model of PV panel is designed based PV mathematical modelling by using single cell diode model. …”
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10
An eigenspace approach for detecting multiple space-time disease clusters: Application to measles hotspots detection in khyber-pakhtunkhwa, Pakistan
Published 2018“…We propose an extension of the EigenSpot algorithm, called Multi-EigenSpot that is able to handle multiple hotspots by iteratively removing previously detected hotspots and re-running the algorithm until no more hotspots are found. …”
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An eigenspace approach for detecting multiple space-time disease clusters: Application to measles hotspots detection in khyber-pakhtunkhwa, Pakistan
Published 2018“…We propose an extension of the EigenSpot algorithm, called Multi-EigenSpot that is able to handle multiple hotspots by iteratively removing previously detected hotspots and re-running the algorithm until no more hotspots are found. …”
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Traffic management algorithms for LEO satellite networks
Published 2016“…In order to evaluate the proposed algorithm, a series of experiments to implement Discrete Event Simulation (DES) of a LEO satellite network by using ns-2 and C/C++ are conducted. …”
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13
Evaluation of genetic algorithm based solar tracking system for photovoltaic panels
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An integrated reservoir modelling and evolutionary algorithm for optimizing field development in a mature fractured reservoir
Published 2016“…The second method is automatic optimization using Genetic Algorithm. That depends on the principle of natural selection as proposed by Darwin The genetic program was coupled with the reservoir flow model to re-evaluate the chosen wells at each iteration until obtaining the optimal choice. …”
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15
Vehicle pick-up and drop-off schedule optimization in a university setting
Published 2024“…For dynamic requests, a handler evaluates acceptance based on time constraints, and schedule re-optimization is triggered as necessary, using the same methods as in the static case. …”
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Robust estimation methods for fixed effect panel data model having block-concentrated outliers
Published 2019“…Two robust Within Group estimators known as Robust Within Group MM (RWMM) and Robust Within Group GM (RWGM) are also proposed to be simulated under the MM-centering. Results of simulation study and real data identify RWMM and RWGM to provide more resistant and efficient estimates under MM-centering compare to the existing estimation based on median centering. …”
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Optimization variation for multiple heuristic approaches in solar tracking
Published 2023Conference paper -
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Performance analysis of PSO MPPT for photovoltaic (PV) system during irradiance changes / Kharismi Burhanudin
Published 2018“…Maximum power point tracking have been widely used to track maximum power from the PV panel. The study focus on extracting maximum power from the PV panel based on the change in solar irradiance absorbed by the PV panel. …”
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20
Analysing the accuracy of machine learning techniques to develop an integrated influent time series model: case study of a sewage treatment plant, Malaysia
Published 2018“…In this research, the influent flow rate of a sewage treatment plant (STP) was modelled and predicted by autoregressive integrated moving average (ARIMA), nonlinear autoregressive network (NAR) and support vector machine (SVM) regression time series algorithms. To evaluate the models’ accuracy, the root mean square error (RMSE) and coefficient of determination (R2) were calculated as initial assessment measures, while relative error (RE), peak flow criterion (PFC) and low flow criterion (LFC) were calculated as final evaluation measures to demonstrate the detailed accuracy of the selected models. …”
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