Search Results - machine ((learning problems) OR (training programmes))

Common mistakes in writing basic elements of C++ programming for dummies / Syarifah Adilah Mohamed Yusoff, Rozita Kadar and Saiful Nizam Warris by Mohamed Yusoff, Syarifah Adilah, Kadar, Rozita, Warris, Saiful Nizam

“…Coding is uniquely suited to training children not just how to solve problems, but also how to express themselves (Resnick, 2019). …”
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Mental health prediction using machine learning: taxonomy,applications, and challenges by Jetli Chung, Jason Teo

“…The increase of mental health problems and the need for effective medical health care have led to an investigation of machine learning that can be applied in mental health problems. )is paper presents a recent systematic review of machine learning approaches in predicting mental health problems. …”
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Development of programmable logic controllers training kit by Aqel, Mohammad O. A., Ismail, Napsiah

“…Programmable Logic Controllers (PLCs) have become the main workhorse for equipment control in a variety of industries since they were introduced in 1968. …”
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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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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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Enhanced Heterogeneous Stacked Ensemble Machine Learning Model For Detecting Nigerian Politically Motivated Cyberhate by Sallau, Mullah Nanlir

“…To solve the identified research gaps from the vantage point of a machine learning researcher, the problem was modelled as a text classification task. …”
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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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A New Probabilistic Output Constrained Optimization Extreme Learning Machine by Wong S.Y., Yap K.S., Li X.C.

“…Benchmarking; Classification (of information); Constrained optimization; Decision making; Electric power systems; Iterative methods; Knowledge acquisition; Learning algorithms; Pattern recognition; Probability; Confidence threshold; Decision making process; Extreme learning machine; Machine learning approaches; Pattern classification problems; Post-processing procedure; Power system applications; Probabilistic output; Machine learning…”

Neural Network Multi Layer Perceptron Modeling For Surface Quality Prediction in Laser Machining by Sivarao, Subramonian

“…The researchers conducted the prediction of laser machining quality, namely surface roughness with seven significant parameters to obtain singleton output using machine learning techniques based on Quick Back Propagation Algorithm. …”
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Technology Entrepreneurship (ENT600) Analysis on laundry service / Abdul Zahier Ismail, Muhammad Syafiq khusairi and Mohamad Nizar Mohd Naim. by Ismail, Abdul Zahier, khusairi, Muhammad Syafiq, Mohd Naim, Mohamad Nizar

“…The training kit have a pneumatic and programmable logic controller (PLC) system that help consumer in electrical wiring issue by troubleshooting problems with the machine. …”
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Systematic review of using machine learning in imputing missing values by Alabadla, Mustafa, Sidi, Fatimah, Ishak, Iskandar, Ibrahim, Hamidah, Affendey, Lilly Suriani, Che Ani, Zafienas, A. Jabar, Marzanah, Bukar, Umar Ali, Devaraj, Navin Kumar, Muda, Ahmad Sobri, Tharek, Anas, Omar, Noritah, Mohd Jaya, Mohd Izham

“…Novel proposed machine learning approaches used for data imputation are analyzed and summarized to assist researchers in selecting a proper machine learning method based on several factors and settings. …”
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Machine learning for all : Practical steps using MATLAB by Abdullah, Abdul Rahim, Shair, Ezreen Farina, Kandaya, Shaarmila, Rahman, Kazi Ashikur

“…This book, Machine Learning for All: Practical Steps Using Matlab, is written for anyone who wants to learn how to apply machine learning using MATLAB. …”
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The application of support vector machine in classifying potential archers using bio-mechanical indicators by Abdullah, Prof. Madya Dr. Mohamad Razali

“…This study classifies potential archers from a set of bio-mechanical indicators trained via different Support Vector Machine (SVM) models. 50 youth archers drawn from a number of archery programmes completed a one end archery shooting score test. …”
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Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

“…Automated machine learning is a promising approach widely used to solve classification and prediction problems, which currently receives much attention for modification and improvement. …”
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Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

“…Automated machine learning is a promising approach widely used to solve classification and prediction problems, which currently receives much attention for modification and improvement. …”
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Neural Network Based Pattern Recognition in Visual Inspection System for Intergrated Circuit Mark Inspection by Sevamalai, Venantius Kumar

“…The neural networks c1assifier was very successful in classifying 1 3 different image patterns by learning from 4 training patterns. The classifier also clocked an average speed of 9.6ms which makes it feasible to implement it on the production floor. …”
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Performance analysis of machine learning algorithms for missing value imputation by Zainal Abidin, Nadzurah, Ismail, Amelia Ritahani, Emran, Nurul Akmar

“…In this paper, the performance of three machine learning classifiers (K-Nearest Neighbors (KNN), Decision Tree, and Bayesian Networks) are compared in terms of data imputation accuracy. …”
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Immune-based technique for undergraduate programmes recommendation / Muhammad Azrill Mohd Zamri by Mohd Zamri, Muhammad Azrill

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Lightweight block cipher security evaluation based on machine learning classifiers and active s-boxes by Lee T.R., Teh J.S., Jamil N., Yan J.L.S., Chen J.

Particle Swarm Optimization in Machine Learning Prediction of Airbnb Hospitality Price Prediction by Masrom, S., Baharun, N., Razi, N.F.M., Rahman, R.A., Abd Rahman, A.S.

“…Particle Swarm Optimization is useful to optimize the best variables combination for automating the features selection in machine learning models. By comparing the magnitude of change of the R squared values before and after the use of PSO feature selection, the result showed that the automated features selection has improved the results of all the machine learning algorithms mainly in the linear-based machine learning (Linear Regression, Lasso, Ridge). …”
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