Search Results - (( data optimization based algorithm ) OR ( data integration learning algorithm ))

Approach For Optimizing Course Recommendation Based On Integrating Modified Felder-Silverman Learning Style Model With Meta-Heuristics Algorithm by Ashraf, Erum

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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…Based on the results obtained, a better prediction result can be produced by the proposed GA-BPNN learning algorithm.…”
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A new variant of black hole algorithm based on multi population and levy flight for clustering problem by Haneen Abdul Wahab, Abdul Raheem

“…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems. …”
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Hybrid weight deep belief network algorithm for anomaly-based intrusion detection system by Maseer, Ziadoon Kamil

“…The optimized DBN algorithm, known as the HW-DBN algorithm, integrated through feature learning based on a Gaussian–Bernoulli Restricted Boltzmann Machine as well as classification task through a weight neuron network. …”
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An Optimal Scheduling Controller for Virtual Power Plant and Microgrid Integration Using the Binary Backtracking Search Algorithm by Abdolrasol M.G.M., Hannan M.A., Mohamed A., Amiruldin U.A.U., Abidin I.B.Z., Uddin M.N.

ANN-Based Binary Backtracking Search Algorithm for VPP Optimal Scheduling and Cost-Effective Evaluation by Hannan M.A., Abdolrasol M.G., Mohamed R., Al-Shetwi A., Ker P., Begum R., Muttaqi K.

Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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Optimizing sentiment analysis of Indonesian texts: Enhancing deep learning models with genetic algorithm-based feature selection by Siti, Mujilahwati, Noor Zuraidin, Mohd Safar, Ku Muhammad Naim, Ku Khalif, Nasyitah, Ghazalli

“…This study examines the optimization of Indonesian text sentiment analysis through the integration of feature selection using a genetic algorithm (GA) with deep learning models. …”
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Job position prediction based on skills and experience using machine learning algorithm / Ezaryf Hamdan by Hamdan, Ezaryf

“…Text preprocessing ensures consistent data representation and facilitates validation. The Machine Learning algorithm, comprising Random Forest, Linear Regression, XGBoost, SVM, and Stacking Ensemble, is embedded in the system for job position predictions based on the analysed data. …”
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An improved teaching-learning-based optimization for extreme learning machine in floating photovoltaic power forecasting by Mohd Redzuan, Ahmad, Nor Farizan, Zakaria, Mohd Shawal, Jadin, Mohd Herwan, Sulaiman

“…This study presents an improved teaching-learning-based optimization algorithm with extreme learning machine for floating photovoltaic power forecasting. …”
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

“…The solution set (i.e. optimized weight/bias matrix of ANN) provided by the optimized and improved genetic algorithm and modified BP based model is extracted and used in the design and development of a prototype device of the proposed model. …”
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IOT-based fertigation system / Mohamad Amir Furqan Darus by Darus, Mohamad Amir Furqan

“…Using advanced algorithms and machine learning techniques, the system nalyses the collected data to determine optimal irrigation and fertilization requirements. …”
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Enhanced computational methods for detection and interpretation of heart disease based on ensemble learning and autoencoder framework / Abdallah Osama Hamdan Abdellatif by Abdalla Osama , Hamdan Abdellatif

“…This approach integrates a conditional variational autoencoder (CVAE) to effectively balance the dataset and a stack predictor (SPFHD) that utilizes tree-based ensemble learning algorithms. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

“…Therefore, we propose a prominent approach that integrates each of the NN, a meta-heuristic based on an evolutionary genetic algorithm (GA), and a core online-offline clustering (Core). …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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Optimizing the production of valuable metabolites using a hybrid of constraint-based model and machine learning algorithms : A review by Kauthar, Mohd Daud, Ananda, Ridho, Suhaila, Zainudin, Chan, Weng Howe, Moorthy, Kohbalan, Nurul Izrin, Md Saleh

“…This review paper summarizes research on the hybrid of constraint-based models and machine learning algorithms in optimizing valuable metabolites. …”
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Optimal variational mode decomposition and integrated extreme learning machine for network traffic prediction by Jinmei Shi, Yu-Beng Leau, Kun Li, Huandong Chen

“…Given this context, this paper proposes a network traffic prediction mechanism based on optimized Variational Mode Decomposition (VMD) and Integrated Extreme Learning Machine (ELM). …”
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Hyper-heuristic framework for sequential semi-supervised classification based on core clustering by Adnan, Ahmed, Muhammed, Abdullah, Abd Ghani, Abdul Azim, Abdullah, Azizol, Huyop @ Ayop, Fahrul Hakim

“…Existing stream data learning models with limited labeling have many limitations, most importantly, algorithms that suffer from a limited capability to adapt to the evolving nature of data, which is called concept drift. …”
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Enhancing project completion date prediction using a hybrid model: rule-based algorithm and machine learning algorithm by Abd Rahman, Mohd Shahrizan, Jamaludin, Nor Azliana Akmal, Zainol, Zuraini, Tengku Sembok, Tengku Mohd

“…The study employs a hybrid predictive model that combines Big Data technologies, Extract Load Transfer (ELT) processes, rule-based algorithms (RBA), machine learning (ML), and Power BI visualizations. …”
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