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Development of intelligent hybrid learning system using clustering and knowledge-based neural networks for economic forecasting : First phase
Published 2004“…We proposed KMeans clustering algorithm that is based on multidimensional scaling, joined with neural knowledge based technique algorithm for supporting the learning module to generate interesting clusters that will generate interesting rules for extracting knowledge from stock exchange databases efficiently and accurately.…”
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Parallel Implementation of Two Level Barotropic Models Applied to the Weather Prediction Problem
Published 2004“…To process the data collected from British Atmospheric Data Centre (BADC), the sequential programs in row and columnwise fashions are developed and implemented. Then the parallel algorithms are constructed and run using the Beowulf Cluster machine. …”
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Thesis -
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The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data
Published 2024“…Therefore, we develop a Parallel Fuzzy C-Median Clustering Algorithm Using Spark for Big Data that can handle large datasets while maintaining high accuracy and scalability. …”
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An Effective Power Dispatch Strategy for Clustered Micro-grids while Implementing Optimal Energy Management and Power Sharing Control using Power Line Communication
Published 2019“…This paper proposes an effective power dispatch strategy for clustered micro-grids. The developed hybrid algorithm implements optimal energy management and power sharing control using binary data. …”
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Smart Agriculture Economics and Engineering: Unveiling the Innovation Behind AI-Enhanced Rice Farming
Published 2024“…Subsequently, the selected superior modified stacked ensemble MLR-SVR-based algorithms are utilized to forecast the 5-year future rice production for each low-middle and upper-middle Southeast Asia nation. …”
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An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction
Published 2023“…In the second method, a new traffic estimation method is proposed using Fuzzy C-Mean (FCM) clustering and Minimum Description Length (MDL). MDL uses patterns to express the repeated presence in the data of particular items or clusters. …”
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Reservoir Inflow Forecasting Using Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System Techniques
Published 2007“…A feed forward Artificial Neural Network (ANN) and an Adaptive Neuro-Fuzzy Inferences System (ANFIS) reservoir inflow models were developed to investigate their potential in forecasting reservoir inflows. …”
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Energy Management Strategies for Optimal Hybrid Microgrid Configuration in the Smart Village Context
Published 2018“…A part of the developed algorithm is used to deal with the optimal scheduling control while the other actuates the dynamic demand response based PV power forecasting. …”
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