Search Results - (( affecting implementation developing algorithm ) OR ( learning implementation based algorithm ))
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Development of lung cancer prediction system using meta-heuristic optimized deep learning model
Published 2023“…Finally, the classification is implemented using an ensemble classifier, deep learning instantaneously trained a neural network and an Autoencoder-based Recurrent Neural Network (ARNN) classification algorithm. …”
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Extreme learning machine for user location prediction in mobile environment
Published 2011“…Moreover, the new framework based on ELM has been compared with the k-Nearest Neighbor and the results have shown that the proposed model based on the extreme learning algorithm outperforms the k-Nearest Neighbor approach. …”
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Extreme learning machine for user location prediction in mobile environment
Published 2011“…Moreover, the new framework based on ELM has been compared with the k-Nearest Neighbor and the results have shown that the proposed model based on the extreme learning algorithm outperforms the k-Nearest Neighbor approach. …”
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Mobile app of mood prediction based on menstrual cycle using machine learning algorithm / Nur Hazirah Amir
Published 2019“…It implemented Supervised Learning algorithm with Bayes’ Theorem model for the calculation of mood prediction using Python programming language. …”
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Prediction models of heritage building based on machine learning / Nur Shahirah Ja'afar
Published 2021“…These algorithms were developed by using prewar shophouses dataset from 2004 until 2018 based on factors of heritage properties. …”
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Polymorphic malware detection based on dynamic analysis and supervised machine learning / Nur Syuhada Selamat
Published 2021“…The benefit of this work indicated that the implementation of a feature selection technique plays an important role in machine learning algorithms to increase the performance of detection.…”
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Poverty risk prediction based on socioeconomic factors using machine learning approach
Published 2025“…This study seeks to develop a predictive model of measuring poverty risk using socioeconomic factors based on a machine learning framework. …”
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A review article on software effort estimation in agile methodology
Published 2021“…The implementation of all machine learning methods used a hybrid approach, which is a combination of machine learning and expert judgement, or a mix of two or more machine learning. …”
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A review article on software effort estimation in agile methodology
Published 2021“…The implementation of all machine learning methods used a hybrid approach, which is a combination of machine learning and expert judgement, or a mix of two or more machine learning. …”
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An improved diabetes risk prediction framework : An Indonesian case study
Published 2018“…In the learning section,Support Vector Machine and Artificial Neural Network were selected as suitable classification algorithms,while Gradient Boosted Tree was employed to interpret the rule based on the black box classifiers.Testing the framework involved Pima Indian Dataset as public dataset and Semarang Hospital Dataset as private dataset (800 patients’ data).In validating the DRPF,four case studies investigated Subject Matter Expert (SME) groups based on the agreement level.The questionnaire consists of a DRPF component,implementation of DRPF,and viability of DRPF.DRPF components were validated by the SMEs,whereby the group ascertained five highest risk factors:HbA1c,systole/diastole,blood glucose,and creatinine and blood urea nitrogen that were assigned by attribute weighting.Results from the questionnaire revealed an average agreement level of 80%. …”
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Hybrid neural network in medicolegal degree of injury determination based on Visum et Repertum
Published 2023“…Then, the selection of the critical features is chosen via Neural Network (NN) as classification algorithm and Genetic Algorithm (GA) as an optimization technique. …”
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Face reidentification system to track factory visitors using OpenVINO
Published 2020“…In addition, as the datasets grow larger, traditional neural network prediction methods will no longer be accurate and fast enough. OpenVINO affect the performance of inference, OpenVINO optimizes multiple calls in the traditional computer vision algorithm implemented in OpenCV, and performs specific optimizations for deep learning inference. …”
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UiTM research supervisor recommendation system / Ahmad Adam Ahmad Muzzlini
Published 2022“…By implementing machine learning content-based filtering to filter the similarities using cosine similarity algorithm and web scraping to obtain the needed supervisor dataset, the system can utilize this information and recommend the suitable potential supervisor for the student. …”
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Transfer learning in near infrared spectroscopy for stingless bee honey quality prediction across different months
Published 2024“…Next, joint distri bution adaptation based partial least square (JDA-PLS) and transfer component analysis based PLS (TCA-PLS) were implemented to establish NIRS predictive models of moisture, hydroxymethylfurfural (HMF), and glucose quality. …”
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A resource-aware content adaptation approach for e-learning environment / Mohd Faisal Ibrahim
Published 2017“…The results showed that the decision algorithm improves the measurement by 28% and the degraded transcoded video does not affect students' comprehension.…”
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Computer-assisted pterygium screening system: a review
Published 2022“…During the early stage of automated pterygium screening system development, conventional machine learning techniques such as support vector machines and artificial neural networks are the de facto algorithms to detect the presence of pterygium tissues. …”
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