Search Results - (( problem learning models algorithm ) OR ( java application stemming algorithm ))

Multi-step time series prediction using recurrent kernel online sequential extreme learning machine / Liu Zongying by Liu , Zongying

“…Besides, concept drift problem in on-line learning model is solved by Drift Detection Machine (DDM). …”
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Hybrid data regression model based on the generalized adaptive resonance theory neural network by Wong S.Y., Yap K.S., Lim C.P., Lee E.W.M.

Classification model for water quality using machine learning techniques by Azilawati, Rozaimee, Azrul Amri, Jamal, Azwa, Abdul Aziz

“…This article proposes a suitable classification model for classifying water quality based on the machine learning algorithms. …”
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

“…The class is known, but it is hidden from the learning model. Unlike supervised, unsupervised directly build the learning model for unlabeled example. …”
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Automated bilateral negotiation with incomplete information in the e-marketplace. by Jazayeriy, Hamid

“…This algorithm comes with some corollaries that form a learning approach in one-side incomplete problem. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. Based on the results obtained, a better prediction result can be produced by the proposed GA-BPNN learning algorithm.…”
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

“…Teaching learning-based optimization is one of the widely accepted metaheuristic algorithms inspired by teaching and learning within classrooms. …”
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Enhancing problem-solving skills of novice programmers in an introductory programming course by Malik S.I., Mathew R., Al-Sideiri A., Jabbar J., Al-Nuaimi R., Tawafak R.M.

Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui by Yang , Dong Rui

“…One of the major research problems is the computation resources required by machine learning algorithm used for classification for HAR. …”
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Meta-heuristics and deep learning for energy applications: Review and open research challenges (2018?2023) by Hosseini E., Al-Ghaili A.M., Kadir D.H., Gunasekaran S.S., Ahmed A.N., Jamil N., Deveci M., Razali R.A.

“…The synergy between deep learning and meta-heuristic algorithms presents a promising avenue for tackling the complexities of energy-related modeling and forecasting tasks. …”

Multi-Backpropagation network by Wan Ishak, Wan Hussain, Siraj, Fadzilah, Othman, Abu Talib

“…Synonym to human learning, a complex problem required some time to learn or memorize. …”
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Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.] by Mohd, Thuraiya, Jamil, Syafiqah, Masrom, Suraya, Ab Rahim, Norbaya

“…In the cycle of Industrial Revolution 4.0 (IR 4.0), many issues in the industries can be solved with implementation of artificial intelligence approaches, including machine learning models. Designing an effective machine learning model for prediction and classification problems is a continuous effort. …”
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Self learning neuro-fuzzy modeling using hybrid genetic probabilistic approach for engine air/fuel ratio prediction by Al-Himyari, Bayadir Abbas

“…The model was compared to other learning algorithms for NFS such as Fuzzy c-means (FCM) and grid partition algorithm. …”
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A modified generalized RBF model with EM-based learning algorithm for medical applications by Ma, Li Ya, Abdul Rahman, Abdul Wahab, Quek, Chai

“…An EM-based training algorithm is also introduced, which uses fewer parameters compared to some classical supervised learning methods. …”
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Comparison of Electricity Load Prediction Errors Between Long Short-Term Memory Architecture and Artificial Neural Network on Smart Meter Consumer by Salleh N.S.M., Suliman A., J�rgensen B.N.

Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol by Md Fisol, Nur Atiqah Izzati

“…Children abandoned in vehicles is a critical issue that has led to numerous fatal injuries worldwide. To address this problem, an optimized in-car-abandoned children's sounds detection model using deep learning algorithms is proposed. …”
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Improved rsync algorithm to minimize communication cost using multi-agent systems for synchronization in multi-learning management systems by Mwinyi, Amir Kombo

“…To meet this requirement, a new Multi LMS (MLMS) model using Sharable Content Object Reference Model (SCORM) specifications to share learning materials among different higher learning institutions (HLIs) has been presented. …”
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Binary ant colony optimization algorithm in learning random satisfiability logic for discrete hopfield neural network by Gao, Yuan, Mohd Kasihmuddin, Mohd Shareduwan, Chen, Ju, Zheng, Chengfeng, Romli, Nurul Atiqah, Mansor, Mohd. Asyraf, Zamri, Nur Ezlin

“…It aimed to optimize the performance of G-type random high-order satisfiability logic structures embedded in Discrete Hopfield Neural Networks, thereby enhancing the efficiency of the Hopfield Neural Network learning algorithm. Through comparative analysis with other metaheuristic algorithms, our model demonstrated superior performance in terms of global convergence, time complexity, and algorithm complexity. …”
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A machine learning approach to tourism recommendations system by Chia, An

“…This project aims to develop a tourism attractions recommendation system by integrating machine learning recommendation algorithms. The main problem encountered when developing a powerful recommendation system is cold start problem, data sparsity and scalability problems. …”
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Modeling a problem solving approach through computational thinking for teaching programming / Zebel Al Tareq by Zebel , Al Tareq

“…The problem-based and the game-based programming workshops utilizing our problem-solving model using sorting algorithms were the experimental groups. …”
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