Search Results - (( data optimization based algorithm ) OR ( parameter evaluation case algorithm ))

Evaluating Bees Algorithm for Sequence-based T-way Testing Test Data Generation by M. H., Mohamed Zabil, Kamal Z., Zamli, K. C., Lim

“…Therefore, test data generation for t-way testing need to be optimized. …”
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T-way testing : a test case generator based on melody search algorithm by Toh, Shu Yuen

“…Next, TTT-MS will be executed through main algorithms to generate Parameters Interaction List, Parameter Values Interaction List, and finally generate final Test Cases based on Melody Search Algorithm. …”
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An online density-based clustering algorithm for data stream based on local optimal radius and cluster pruning by Islam, Md Kamrul

“…To evaluate the performance, BOCEDS algorithm is executed on two syntactic and one practical data streams. …”
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An Improved Hybrid of Particle Swarm Optimization and the Gravitational Search Algorithm to Produce a Kinetic Parameter Estimation of Aspartate Biochemical Pathways by Ahmad Muhaimin, Ismail, Mohd Saberi, Mohamad, Hairudin, Abdul Majid, Khairul Hamimah, Abas, Safaai, Deris, Zaki, Nazar, Siti Zaiton, Mohd Hashim, Zuwairie, Ibrahim, Muhammad Akmal, Remli

“…The results show that the proposed algorithm outperformed other standard optimization algorithms in terms of accuracy and near-optimal kinetic parameter estimation. …”
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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.

A hybrid model using genetic algorithm and neural network for predicting dengue outbreak by Husin, Nor Azura, Mustapha, Norwati, Sulaiman, Md. Nasir, Yaakob, Razali

“…Sample data that covers dengue and rainfall data of five districts in Selangor collected from State Health Department of Selangor (SHD) and Malaysian Meteorological Department is used as a case study to evaluate the proposed model. …”
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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. …”

Using scatter search algorithm in implementing examination timetabling problem by Mohammed M.A., Ghani M.K.A., Mostafa S.A., Ibrahim D.A.

“…The study investigates the most suitable parameters of Scatter Search algorithm for the population based algorithm. …”

Energy management scheduling for microgrids in the virtual power plant system using artificial neural networks by Abdolrasol M.G.M., Hannan M.A., Suhail Hussain S.M., Ustun T.S., Sarker M.R., Ker P.J.

Optimisation of laser cutting parameters of oil palm wood / Harizam Mohd Zin by Harizam, Mohd Zin

“…The simulation results were evaluated and verified with the experiment. In some cases, the prediction errors of Taguchi ANN model was found larger than 10% even using a Levenberg Marquardt training algorithm. …”
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Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems by Uvaraja, Vikneswary

“…The MTS algorithm is coded in ANSI-C language and tested on benchmark data from Mandl's Swiss Network and Mumford's larger data. …”
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Modified word representation vector based scalar weight for contextual text classification by Abbas Saliimi, Lokman

“…To validate this algorithm, the modified word vectors are compared with original LLM-generated word vectors to evaluate their reflection of the intended context. …”
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Optimized techniques for landslide detection and characteristics using LiDAR data by Mezaal, Mustafa Ridha

“…Also, six techniques: Ant Colony Optimization (ACO), Gain Ratio (GR), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), Random forest (RF), and Correlation-based Feature Selection (CFS) were used for the feature selection. …”
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Workload performance evaluation of large spatial database for DSS based disaster management by Rohman, Muhammad Syaifur

“…Additionally, the results of the study indicated that the prediction model for workload performance evaluation using CBR that is optimized with Hash Search technique for determining workload data on Shortest Path analysis via the employment of Dijkstra algorithm can be useful for the prediction of incoming workload based on the status of the DBMS parameters. …”
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

Integration of knowledge-based seismic inversion and sedimentological investigations for heterogeneous reservoir by Shahbazi, A., Monfared, M.S., Thiruchelvam, V., Ka Fei, T., Babasafari, A.A.

“…The back propagation algorithm and the fuzzy neural network are also used in the methodology for parameter optimization and definition of nonlinear relationship between seismic attributes and porosity of the reservoir rock. …”
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Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller by Zaridah, Mat Zain

“…It is observed that the APFLC showed convincing performance over the entire simulation of the Pico-satellite. Genetic Algorithm (GA) is a computational model inspired by evaluation. …”
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An efficient network mobility management for a 6LoWPAN mobile network in hospital environments by Shahamabadi, Mohammadreza Sahebi

“…The second scheme is a message-scheduling algorithm based on route optimization in tunnelling process between the MNNs and HA to decrease the traffic congestion at MR and packet end-toend delay. …”
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Air quality forecasting and mapping in Malaysian urban areas: A hybrid deep learning approach by Nur'atiah Zaini

Development of data-driven controller for slosh suppression in liquid cargo vehicles by Mohd Falfazli, Mat Jusof, Ahmad, Mohd Ashraf, Raja Ismail, R. M.T., Suid, Mohd Helmi, Saari, Mohd Mawardi

“…Then, this research report focuses on assessing the effectiveness of the SED-based algorithm for data-driven proportional-integral derivative (PID) control tuning in liquid slosh problems. …”
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