Search Results - (( developing nation machine algorithm ) OR ( java implication based algorithm ))

Sentiment analysis on national cultural tourism using Linear Support Vector Machine (LSVM) / Nur Haida Hanna Samsuddin by Samsuddin, Nur Haida Hanna

“…A classifier will be designed and developed which is Linear Support Vector Machine (LSVM). …”
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Wearable based-sensor fall detection system using machine learning algorithm by Ishak, Anis Nadia, Habaebi, Mohamed Hadi, Yusoff, Siti Hajar, Islam, Md. Rafiqul

“…To prevent such kinds of deadly scenarios, a reliable fall detection system must be developed to help many lives. In this project, a wearable sensor-based fall detection system using a machine-learning algorithm had been developed. …”
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Develpoment of combinatorial optimisation for cutting tool path strategy by Alsultaney, Hazem K., Mohd Ariffin, Mohd Khairol Anuar, Baharudin, B. T. Hang Tuah, Ali, Aidy, Mustapha, Faizal

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Poverty Classification of Central Perak Population Using Machine Learning by P.Rajendran, Kumaran

“…The picture of Central Perak development reveals many families are not benefiting from national economic growth. …”
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Harmony Search algorithm-based gasoline consumption modeling for Indonesia by Anggarani, Riesta, Watada, Junzo

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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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A WEB-BASED SYSTEM FOR THE PREDICTION OF STUDENT PERFORMANCE IN UPCOMING PUBLIC EXAMS BASED ON ACADEMIC RECORDS by DELLON, NELSON BRUNNIE

“…Teachers will be able to precisely forecast their students' impending grades utilizing the system's web-based application integration and machine learning algorithms. The machine learning algorithms that will be used and compared are Support Vector Machines (SVM), Random Forest (RF), K-Nearest Neighbors (KNN), Artificial Neural Network (ANN), and Linear Regression (LR). …”
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Investigating photovoltaic solar power output forecasting using machine learning algorithms by Essam Y., Ahmed A.N., Ramli R., Chau K.-W., Idris Ibrahim M.S., Sherif M., Sefelnasr A., El-Shafie A.

“…To address this issue, continuous research and development is required to determine the best machine learning (ML) algorithm for PV solar power output forecasting. …”

An improved vulnerability exploitation prediction model with novel cost function and custom trained word vector embedding by Hoque M.S., Jamil N., Amin N., Lam K.-Y.

Utilizing machine learning to predict hospital admissions for pediatric COVID-19 patients (PrepCOVID-Machine) by Chuin-Hen Liew, Song-Quan Ong, David Chun-Ern Ng

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Robust Data Fusion Techniques Integrated Machine Learning Models For Estimating Reference Evapotranspiration by Chia, Min Yan

“…As for the NNE, a novel meta-learner based on the stochastic-enabled extreme learning machine integrated with whale optimisation algorithm (WOA-ELM) was developed and used in such an application for the first time. …”
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Classification of imbalanced travel mode choice to work data using adjustable svm model by Qian, Y., Aghaabbasi, M., Ali, M., Alqurashi, M., Salah, B., Zainol, R., Moeinaddini, M., Hussein, E.E.

“…This study deals with imbalanced mode choice data by developing an algorithm (SVMAK) based on a support vector machine model and the theory of adjusting kernel scaling. …”
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Machine learning-based risk prediction model for medication administration errors in neonatal intensive care units: a prospective direct observational study by Henry Basil, Josephine, Lim, Wern Han, Syed Ahmad, Sharifah M., Menon Premakumar, Chandini, Mohd Tahir, Nurul Ain, Mhd Ali, Adliah, Seman, Zamtira, Ishak, Shareena, Mohamed Shah, Noraida

“…Each observation was independently assessed for errors. Ten machine learning (ML) algorithms were applied with features derived from systematic reviews, incident reports, and expert consensus. …”
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Green building factor in machine learning based condominium price prediction by Masrom, S., Mohd, T., Rahman, A.S.A.

“…To predict a housing price, a robust approach is crucial, which can be effectively gained from the machine learning technique. As research on green building with machine learning techniques is rarely reported in the literature, this paper presents the fundamental design and the comparison results of three machine learning algorithms namely deep learning (DL), decision tree (DT), and random forest (RF). …”
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Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization by Nanyonga Aziida, Sorayya Malek, Firdaus Aziz, Khairul Shafiq Ibrahim, Sazzli Kasim

“…Feature selection methods such as Boruta, Random Forest (RF), Elastic Net (EN), Recursive Feature Elimination (RFE), learning vector quantization (LVQ), Genetic Algorithm (GA), Cluster Dendrogram (CD), Support Vector Machine (SVM) and Logistic Regression (LR) were combined with RF, SVM, LR, and EN classifiers for 30-day mortality prediction. …”
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Investment, trade and exchange rates / Noor Zahirah Mohd Sidek and Mahadzir Ismail by Mohd Sidek, Noor Zahirah, Ismail, Mahadzir

“…Finally, the robustness of the model (s) and the estimation of the threshold value (s) are conducted using heuristic approaches of genetic algorithm, neuro network and support vector machine. …”
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Poverty Classification in Indonesia Using BiGRU, BPNN, and Stacking AdaBoost Frameworks by Khalisha, Ariyani, Silvia, Ratna, M., Muflih, Haldi, Budiman, Noor, Azijah, M.Rezqy, Noor Ridha

“…These findings underscore the critical role of machine learning in formulating effective policies for poverty alleviation and suggest that integrating multiple machine learning algorithm can significantly enhance decision-making processes. …”
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Machine learning based return prediction for digital financial portfolios by LinXi Shi, Thien Sang Lim, Jin Yan, Pengcheng Qi, Tao Li

“…Therefore, this paper selects the returns and risks of digital financial investment as the research topic and predicts the investment returns of the five major online banks by analyzing the digital financial portfolio investment return prediction system. The machine learning algorithm is introduced to optimize the digital financial portfolio investment return prediction system. …”
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Faulty classification system for VTOL UAV acoustic signal using machine learning by Makhtar, Siti Noormiza, Mohd Sani, Fareisya Zulaikha, Nor, Elya Mohd, Kamarudin, Nur Diyana, Md Ali, Syaril Azrad

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Predicting mortality of Malaysian patients with acute coronary syndrome (ACS) subtypes using machine learning and deep learning approaches / Muhammad Firdaus Aziz by Muhammad Firdaus , Aziz

“…The purpose of this study is to use machine learning (ML) and deep learning (DL) algorithms to predict and identify variables linked to short and long-term mortality in Asian STEMI and NSTEMI/UA patients and to compare these results to a conventional risk score. …”
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