Search Results - (( variable reduction within algorithm ) OR ( java application optimisation algorithm ))

Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Enhancing Harmony Search Metaheuristic Algorithm for Coverage Efficiency, Test Suite Reduction, and Running Time in Combinatorial Interaction Testing by Muazu, Aminu Aminu, Hashim, Ahmad Sobri

“…The experimental results demonstrate that eHS outperforms the other algorithms for CIT in terms of coverage efficiency and test suite reduction. …”
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Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management by almahameed, Bader aldeen, Bisharah, Majdi

“…Particle Swarm Optimization (PSO) has demonstrated its efficacy in addressing the issue of construction waste reduction and enhancing the accuracy of cost estimation through the identification of optimal combinations of variables. …”
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Conceptual Design And Dynamical Analysis Of Aerostat System by Mahmood, Khurrum

“…The optimized configuration of the aerostat shows a reduction in volume to 120 m3 from 170 m3, reduction in mass to 71.6 kg from 90.65 kg. …”
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A Hybrid Adaptive Leadership GWO Optimization with Category Gradient Boosting on Decision Trees Algorithm for Credit Risk Control Classification by Suihai, Chen, Chih How, Bong, Po Chan, Chiu

“…Therefore, this study first reduces the dimension of the variable features (deleting the variable features with low correlation), and then uses two different datasets for experimental comparison and verification, which proves that the dimension reduction can improve the efficiency of the algorithm. …”
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Development of a phantom and metal artifact correction (MAC) algorithm for post-operative spine computed tomography (CT) imaging / Noor Diyana Osman by Osman, Noor Diyana

“…The last part is the development of a metal artifact correction (MAC) algorithm and evaluation of the proposed algorithm in artifacts reduction in CT images. …”
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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 terms of optimization and reduction the experimental data, GAs could get the best lowest value for roughness compared to experimental data with reduction ratio of 46.75%.…”
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Enhancing campus mobility: simulated multi-objective optimization of electric vehicle sharing systems within an intelligent transportation system frameworks by Aba Hussen, Omar S., Hashim, Shaiful J., Sulaiman Member, Nasri, Alhaddad, S.A.R., Ribbfors, Bassam Y., Umeda, Masanobu, Katamine, Keiichi

“…In addition to conventional decision variables, dynamic dual relocation thresholds and charge levels are introduced as decision variables to enhance optimization. …”
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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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Long-term optimal planning for renewable based distributed generators and plug-in electric vehicles parking lots toward higher penetration of green energy technology by ALAhmad A.K., Verayiah R., Shareef H., Ramasamy A.

“…Moreover, to ensure realism, the model incorporates uncertainties related to stochastic variables such as the intermittent nature of RESs, EV energy and time variables, loads, and energy price fluctuations, using Monte Carlo Simulation (MCS) and the backward reduction method (BRM). …”

Comparative Analysis of Artificial Intelligence Methods for Streamflow Forecasting by YAXING, WEI, HUZAIFA, HASHIM, Lai, Sai Hin, CHONG, KAI LUN, HUANG, YUK FENG, ALI NAJAH, AHMED, MOHSEN, SHERIF, AHMED, EL-SHAFIE

“…For this dataset, wavelet transformation significantly improves the resolution of lag noise when historical streamflow data are used as lagged input variables, producing a 6% reduction in the root-mean-square error. …”
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Intelligence Integration Of Particle Swarm Optimization And Physical Vapour Deposition For Tin Grain Size Coating Process Parameters by Abdul Syukor, Mohamad Jaya, Mu*ath Ibrahim, Mohammad Jarrah, Mohd Asyadi Azam, Mohd Abid, Mohd Razali, Muhamad

“…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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Implementation of MRAC, SVMPC and PID control based on direct digital control application for dc servomotor by Mohamad Saleh, Saleha

“…The desired behavior of the adaptive controller is expressed by utilizing reference model, and the algorithms have been realized using the Lyapunov method and MIT rules. …”
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Network reconfiguration and DG sizing incorporating optimal switching sequence for system improvement / Ola Subhi Waheed Badran by Ola Subhi , Waheed Badran

“…Moreover, the voltage profile during the switching sequence process was within the allowable limit.…”
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Optimising Connectivity and Energy : The Future of LoRaWAN Routing Protocols for Mobile IoT Applications by IZZAH NILAMSYUKRIYAH, BUANG, Kartinah, Zen, Syahrul Nizam, Junaini

“…Key topics examined include AI-enhanced adaptive data rate (ADR) methods, coding schemes based on the Chinese Remainder Theorem (CRT), and processes utilizing Variable Order Hidden Markov Models (VHMM). These approaches have demonstrated improvements in packet delivery ratios (PDRs), latency reduction, and energy efficiency within mobile IoT contexts. …”
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Predictive Framework for Imbalance Dataset by Megat Norulazmi, Megat Mohamed Noor

“…Properties of the proposed framework include; developing an approach to correlate materials defects, developing an approach to represent data attributes features, analyzing various ratio and types of data re-sampling, analyzing the impact of data dimension reduction for various data size, and partitioning data size and algorithmic schemes against the prediction performance. …”
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Reduced torque ripple and switching frequency using optimal DTC switching strategy for open-end winding induction machines by Abd Rahim, Muhd Khairi

“…The main benefit of the proposed strategy is its simplicity, where the DTC improvements can be obtained without the common approach, i.e. the use of Space Vector Modulation (SVM) which involves complex control algorithms. It also shown that the average improvement about 39% and 43% can be achieved toward reduction of torque ripple and switching frequency.…”
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