Search Results - machine ((learning problem) OR (learning problems))

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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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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N-job, m-macine lot streaming problem with learning effects by Mortezaei, Navid, Zulkifli, Norzima

“…However, there is not any study about lot streaming problem with learning considerations. In this study, we develop mixed-integer mathematical models for multiple products and multiple machines lot streaming problem with learning considerations. …”
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An interactive analytics approach for sustainable and resilient case studies: a machine learning perspective by Mousavi, Seyed Mohsen, Sadeghi R., Kiarash, Lee, Lai Soon

“…However, there needs to be more research examining the role of interactive methods in multiobjective optimisation problems. To integrate machine learning and human interactions, this paper develops a new three-stage interactive algorithm in business analytics, called the interactive Nautilus-based algorithm, to address complex problems. …”
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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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The Evolutionary Convergent Algorithm: A Guiding Path of Neural Network Advancement by Hosseini E., Al-Ghaili A.M., Kadir D.H., Daneshfar F., Gunasekaran S.S., Deveci M.

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Teaching and learning via chatbots with immersive and machine learning capabilities by Nantha Kumar Subramaniam

“…These chatbots support learning of Java via problem-solving steps through “learning by doing”. …”
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The rise of software vulnerability: Taxonomy of software vulnerabilities detection and machine learning approaches by Hazim, Hanif, Mohd Hairul Nizam, Md Nasir, Mohd Faizal, Ab Razak, Ahmad, Firdaus, Nor Badrul, Anuar

“…However, they lack discussion on the newly trending machine learning approaches, such as supervised learning and deep learning techniques. …”
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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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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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Daily maximum load forecasting of consecutive national holidays using OSELM-based multi-agents system with weighted average strategy by Yap K.S., Yap H.J.

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Investigation of cross-entropy-based streamflow forecasting through an efficient interpretable automated search process by Chong K.L., Huang Y.F., Koo C.H., Sherif M., Ahmed A.N., El-Shafie A.

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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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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.

“…Brain; Errors; Forecasting; Learning algorithms; Mean square error; Memory architecture; Network architecture; Smart meters; Time series; Demand-side; Electricity load; Error values; Load predictions; Machine learning algorithms; Mean absolute error; Mean squared error; Prediction errors; Regression problem; Times series; Long short-term memory…”