Search Results - (( using normalization based algorithm ) OR ( using factorization machine algorithm ))
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Optimal network reconfiguration and intelligent service restoration prediction technique based on Cuckoo search spring algorithm / Mohamad Izwan Zainal
Published 2022“…In this research, Cuckoo Search Spring Algorithm (CSSA) is proposed to enhance the robustness of algorithm by constructing the optimal network reconfiguration consist of reducing power losses and improve voltage profile with the various loadability factor as the constraint according to load profile, based on single and multiobjective model. …”
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2
Visual analysis to investigate the capability of ANFIS in modelling hydrological relationship using synthetic dataset
Published 2018“…In using most of the machine learning algorithms including ANFIS, to obtain the best model, the common and normal approach is always by comparing models of different parameter settings based on the goodness-offit statistical measures. …”
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Designing of prediction model for parameter optimization in cnc machining based on artificial neural network / Armansyah ... [et al.]
Published 2025“…These outputs were then utilized to train an ANN prediction model based on a feed-forward backpropagation (FFBP) algorithm. …”
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Prediction of breast cancer diagnosis using machine learning in Malaysian women
Published 2024“…This project found that there was a strong interest in the application of ML to breast cancer in the last three decades. The three frequently used ML algorithms were deep learning, support vector machine (SVM), and cluster analysis. …”
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5
Predicting Market Trends : A Stock Prices Forecasting with Artificial Neural Network for Apple Inc. and Microsoft Corp.
Published 2025“…The unpredictability of stock price behaviour, influenced by numerous factors, adds complexity to this process. Consequently, numerous studies have explored the use of machine learning for stock price forecasting. …”
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An Improved Diabetes Risk Prediction Framework : An Indonesian Case Study
Published 2018“…Pre-processing resolves the issue of missing data and hence normalizes the data.Outlier treatment employs k-mean clustering to validate the class.Suitable components were selected through comparison of classifier algorithms and feature selection.Attribute weighting based feature selection was selected for assigning weightage.Weighted risk factor was used on training dataset in order to improve accuracy and computation time of the prediction. …”
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Biometric identification and recognition for iris using failure rejection rate (FRR) / Musab A. M. Ali
Published 2016“…Next, select smaller yet optimal and effective normalized iris image size by applying different normalization factors. …”
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A review of machine vision pose measurement
Published 2024“…Discusses the factors that affect the accuracy and reliability of machine vision pose measurement algorithms. …”
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A review of machine vision pose measurement
Published 2024“…Discusses the factors that affect the accuracy and reliability of machine vision pose measurement algorithms. …”
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The influence of sentiments in digital currency prediction using hybrid sentiment-based Support Vector Machine with Whale Optimization Algorithm (SVMWOA)
Published 2021“…Support Vector Machine (SVM) technique is used with the Whale Optimization Algorithm (WOA) which is inspired by the swarm optimization algorithms. …”
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Proceeding Paper -
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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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Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China
Published 2024“…Therefore, this study investigates the capability of various machine learning algorithms in predicting the power production of a reservoir located in China using data from 1979 to 2016. …”
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Optimization of chest X-ray exposure factors using machine learning algorithm
Published 2023“…In this study, the chest X-ray exposure factors for 178 patients with different body mass index (BMI) values have been analyzed using the Python Machine Learning algorithm. …”
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram
Published 2021“…Therefore, this study aimed to used OBIA method with selected machine learning algorithm to estimate the mangrove age by using Sentinel 2A image. …”
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Reverse migration prediction model based on machine learning / Azreen Anuar
Published 2024“…A significant way to minimize the errors is by using a machine learning approach that can predict reverse migration intelligently depending on the tested dataset. …”
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18
Neural Network Multi Layer Perceptron Modeling For Surface Quality Prediction in Laser Machining
Published 2009“…One such method is machine learning, which involves using a computer algorithm to capture hidden knowledge from data. …”
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An alternative approach to normal parameter reduction algorithms for decision making using a soft set theory / Sani Danjuma
Published 2017“…In addition, the algorithm was relatively easy to understand compare to the state of the art of normal parameter reduction algorithm. …”
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JPEG Image Encryption Using Combined Reversed And Normal Direction-Distorted Dc Permutation With Key Scheduling Algorithm-Based Permutation
Published 2008“…The proposed approach uses a frequency domain combinational framework of coefficients scrambling with Key Scheduling Algorithm based (KSA-based) permutation. …”
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