Search Results - (( its implication learning algorithm ) OR ( variable interactive learning algorithm ))

Prediction of payment method in convenience stores using machine learning by Pratondo, Agus, Novianty, Astri, Pudjoatmodjo, Bambang

“…This study explores the application of machine learning techniques, specifically the Random Forest algorithm, to predict payment modes in the context of the Indonesian community. …”
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Tangible interaction learning model to enhance learning activity processes among children with dyslexia by Jamalai@Jamali, Siti Nurliana

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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud by Shariff, S. Sarifah Radiah, Hud, Hady

“…Secondly, in solving every Machine Learning problem, there is no one algorithm superior to other algorithms. …”
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Revolutionizing video analytics: a review of action recognition using 3D by Jeddah, Yunusa Mohammed, Hassan Abdalla Hashim, Aisha, Khalifa, Othman Omran, Ibrahim, Adamu Abubakar

“…It also addresses the practicalities of implementing action recognition algorithms in real-world situations, which include tools like deep learning frameworks, pre-trained models, open-source libraries, cloud services, GPU acceleration, and evaluation metrics. …”
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Neural Network Multi Layer Perceptron Modeling For Surface Quality Prediction in Laser Machining by Sivarao, Subramonian

“…One such method is machine learning, which involves using a computer algorithm to capture hidden knowledge from data. …”
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Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei by Alireza , Pourdaryaei

“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through the use of Backtracking Search Algorithm (BSA) as an efficient optimization algorithm in learning process of ANFIS approach. …”
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Analysis using data mining techniques: the exploration and review data of diabetes patients / Syarifah Adilah Mohamed Yusoff ... [et al.] by Mohamed Yusoff, Syarifah Adilah, Othman, Jamal, Johan, Elly Johana, Mohd Mydin, Azlina, Wan Mohamad, Wan Anisha

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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

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Support vector machine in precision agriculture: a review by Kok, Zhi Hong, Mohamed Shariff, Abdul Rashid, M. Alfatni, Meftah Salem, Bejo, Siti Khairunniza

“…The Support Vector Machine (SVM) is a Machine Learning (ML) algorithm which may be used for acquiring solutions towards better crop management. …”
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Harnessing reinforcement learning in fog-cloud computing: challenges, insights, and future directions by Al-Hashimi, Mustafa, Rahiman, Amir Rizaan, Muhammed, Abdullah, Hamid, Nor Asilah Wati

“…This article explores the different RL algorithms, emphasizing their distinct strengths, weaknesses, and practical implications in fog-cloud environments. …”
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Analyzing enrolment patterns: Stacked ensemble statistical learning-based approach to educational decision making by Chuan, Zun Liang, Chong, Teak Wei, Japashov, Nursultan, Soon, Kien Yuan, Tan, Wei Qing, Noriszura, Ismail, Liong, Choong-Yeun, Tan, Ee Hiae

“…Moreover, the introduction of the novel stacked ensemble machine learning algorithm had improved predictive accuracy compared to traditional dichotomous logistic regression algorithms on average, particularly at optimal training-to-test ratios of 70:30, 80:20, and 90:10. …”
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Age detection from face using Convolutional Neural Network (CNN) / Hanin Hanisah Usok @ Yusoff by Usok @ Yusoff, Hanin Hanisah

“…A user-friendly desktop system is created for input of facial photos and receiving immediate age estimation results, illustrating machine learning's assure in age identification. With implications for personalised services and security, this experiment demonstrates how CNN algorithms improve accuracy, adding to successful age-related technology.…”
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Predicting sea levels using ML algorithms in selected locations along coastal Malaysia by Hazrin N.A., Chong K.L., Huang Y.F., Ahmed A.N., Ng J.L., Koo C.H., Tan K.W., Sherif M., El-shafie A.

“…In consideration of the distinct behavior of machine learning (ML) algorithms, six well-defined ML used were carried out in this study for predicting sea level on a day-to-day basis. …”

Artificial intelligence (AI) and its application in architecture design: a thematic review by Jin, Deran, Zairul, Mohd, Salih, Sarah Abdulkareem

“…Despite the growing number of publications on AI and architectural design, comprehensive reviews are lacking in exploring its evolution, strategies, and future directions. …”
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Electric vehicle battery state of charge estimation using metaheuristic-optimized CatBoost algorithms by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Ahmad Salihin, Samsudin, Amir Izzani, Mohamed, Mohd Mawardi, Saari

“…Three distinct metaheuristic algorithms were investigated: Barnacles Mating Optimizer (BMO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Whale Optimization Algorithm (WOA), each integrated with CatBoost to optimize critical parameters including learning rate, tree depth, regularization, and bagging temperature. …”
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Predicting sea levels using ML algorithms in selected locations along coastal Malaysia by Hazrin N.A, Chong K.L, Huang Y.F, Ahmed A.N, Ng J.L, Koo C.H, Tan K.W, Sherif M, El-shafie A

“…In consideration of the distinct behavior of machine learning (ML) algorithms, six well-defined ML used were carried out in this study for predicting sea level on a day-to-day basis. …”

Not seeing the forest for the trees: Generalised linear model out-performs random forest in species distribution modelling for Southeast Asian felids by Chiaverini, Luca, Macdonald, David W., Hearn, Andrew J., Kaszta, Zaneta, Ash, Eric, Bothwell, Helen M., Can, Ozgun Emre, Channa, Phan, Clements, Gopalasamy Reuben *, Haidir, Iding Achmad, Kyaw, Pyae Phyoe, Moore, Jonathan H., Rasphone, Akchousanh, Tan, Cedric Kai Wei, Cushman, Samuel A.

“…The latter is a machine learning non-parametric algorithm, more tolerant than other approaches in its assumptions, which has often been shown to outperform parametric algorithms. …”
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Machine Learning-based Classification Of Termite Genera by Sundresan A/L Perumal, Homathevi Rahman, Valliappan Raman, Subramanian Raja Nagendran, Bala Saatvik Thanigai Arasu, Deepakkumar Senthil Kumar, Roghan Raja

The Effects Of Segmenting And Computational Thinking In Digital Video Courseware On Knowledge Achievement, Self-Efficacy And Motivation Among Students With Different Thinking Style... by Ali, Wan Nor Ashiqin Wan

“…The researcher found significant main and interaction effects of the learner-paced predefined segment on all dependent variables. …”
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Analysis of daytime and nighttime ground level ozone concentrations using boosted regression tree technique by Yahaya, Noor Zaitun, Ghazali, Nurul Adyani, Ahmad, Sabri, Mohammad Asri, Mohammad Akmal, Ibrahim, Zul Fahdli, Ramli, Nor Azman

“…Sensitivity testing of the BRT model was conducted to determine the best parameters and good explanatory variables. Using the number of trees between 2,500-3,500, learning rate of 0.01, and interaction depth of 5 were found to be the best setting for developing the ozone boosting model. …”
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