Search Results - (( variable integration based algorithm ) OR ( variable active learning algorithm ))

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

“…The performance of ANNs depend on many factors, including the network structure, the selection of activation function, the learning rate of the training algorithm, and initial synaptic weight values, the number of input variables, and the number of units in the hidden layer. …”
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Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance by Allawi, Mohammed Falah, Jaafar, Othman, Mohamad Hamzah, Firdaus, Koting, Suhana, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

“…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
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Risk perception modeling based on physiological and emotional responses / Ding Huizhe by Ding , Huizhe

“…However, when risk degrees were closely matched, the integrated model with weight adjustments based on base models outperformed ANN. …”
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Computational Thinking : Experiences of Rural Pupils in Sarawak Primary School by Nur Hasheena, Anuar

“…The study employed embedded mixed methods design using a quasi-experimental approach which aims to provide an in-depth understanding of how pupils in remote rural area adapt and process to learning Computational Thinking skills (i.e., abstraction, algorithmic thinking, and decomposition) as well as their attitudes towards computational thinking practices by engaging in an unplugged game-based, art-based, Scratch programming and robotic activities through a revised Computational Thinking pedagogical model. …”
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

“…The focus of the paper is to propose a hybrid approach for the selection of the most influential input variables for the training and testing of neural network based hybrid models. …”
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Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic by Yap, Soon Teck

“…These two adaptive routing algorithms enhance the existing Confidence-based Q (CQ) and Confidence-based Dual Reinforcement Q (CDRQ) Routing Algorithms. …”
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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ENGINEERING DESIGN WITH PSO ALGORITHM by MHD BASIR, SITI NUR HAJAR

“…Creating a PSO algorithm-based infrastructure integrating with the recommendation system will further enhance solution to the design problem. …”
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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.

Shunt active power filter using hybrid fuzzy-proportional and crisp-integral control algorithms for total harmonic distortion improvement by Abdul Rahman, Nor Farahaida

“…First, unified ADALINEs based fundamental component extraction algorithm is proposed for dual functionality. …”
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Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio... by Daba, Layth Muwafaq Abdulhussein

“…Unlike the existing optimization algorithm, VL-WIDE features the capability of searching different lengths of solutions to cover the variable number of cloudlets for deployment. …”
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Numerical algorithm of block method for general second order ODEs using variable step size by Nazreen Waeleh, Zanariah Abdul Majid

“…Consequently, a direct block multistep method with utilization of variable step size strategy is proposed. This method was developed for computing the solution at four points simultaneously and the derivation based on numerical integration as well as using interpolation approach. …”
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Examining the potential of machine learning for predicting academic achievement: A systematic review by Nazir, M., Noraziah, Ahmad, Rahmah, M., Sharma, Aditi

“…Predicting student academic performance is a critical area of education research. Machine learning (ML) algorithms have gained significant popularity in recent years. …”
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Examining the potential of machine learning for predicting academic achievement: A systematic review by Nazir, M., Noraziah, Ahmad, Rahmah, M., Sharma, Aditi

“…Predicting student academic performance is a critical area of education research. Machine learning (ML) algorithms have gained significant popularity in recent years. …”
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Classification of students' performance in computer programming course according to learning style by Norwawi N.M., Abdusalam S.F., Hibadullah C.F., Shuaibu B.M.

Numerical algorithm of block method for general second order ODEs using variable step size by Waeleh, Nazreen, Abdul Majid, Zanariah

“…Consequently, a direct block multistep method with utilization of variable step size strategy is proposed. This method was developed for computing the solution at four points simultaneously and the derivation based on numerical integration as well as using interpolation approach. …”
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Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

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SURE-Autometrics algorithm for model selection in multiple equations by Norhayati, Yusof

“…The algorithm is developed by integrating the SURE model with the Autometrics search strategy; hence, it is named as SURE-Autometrics. …”
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An improved neuroendocrine-proportional-integral-derivative controller with sigmoid-based secretion rate for nonlinear multi-input-multi-output crane systems by Mohd Riduwan, Ghazali, Mohd Ashraf, Ahmad, Raja Mohd Taufika, Raja Ismail, Tokhi, M. O.

“…The performance of the proposed sigmoid-based secretion rate neuroendocrine–proportional–integral–derivative controller-based safe experimentation dynamics algorithm is evaluated by tracking the error and the control input. …”
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