Search Results - (( regression estimation using algorithm ) OR ( java application using algorithm ))

Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm by Hossain Lipu M.S., Hannan M.A., Hussain A., Ansari S., Rahman S.A., Saad M.H.M., Muttaqi K.M.

“…This paper presents an improved machine learning approach for the accurate and robust state of charge (SOC) in electric vehicle (EV) batteries using differential search optimized random forest regression (RFR) algorithm. …”

RSA Encryption & Decryption using JAVA by Ramli, Marliyana

“…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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Credit scoring for Cooperative of financial services using logistic regression estimated by genetic algorithm by Mustafa, Mamat, Sukono, Firman, Asep, Sholahuddin

“…To anticipate the risk of default (credit risk), to prospective debtors applying for credit risk analysis was performed using credit scoring. In this paper the analysis of credit scoring is done using logistic regression model, which is estimated using genetic algorithms. …”
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Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

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Provider independent cryptographic tools by Ibrahim, Subariah, Salleh, Mazleena, Abdul Aziz, Shah Rizan

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Differential Search Optimized Random Forest Regression Algorithm for State of Charge Estimation in Electric Vehicle Batteries by Hossain Lipu M.S., Hannan M.A., Hussain A., Ansari S., Ayob A., Saad M.H.M., Muttaqi K.M.

Machine Learning Regression Approach for Estimating Energy Consumption of Appliances in Smart Home by Husin N.S.I.M., Mostafa S.A., Jaber M.M., Gunasekaran S.S., Al-Shakarchi A.H., Abdulsattar N.F.

“…This paper attempts to use machine learning algorithms to estimate the energy consumption of appliances in a smart home environment. …”

Evaluating enhanced predictive modeling of foam concrete compressive strength using artificial intelligence algorithms by Abdellatief M., Wong L.S., Din N.M., Mo K.H., Ahmed A.N., El-Shafie A.

“…In this context, linear regression (LR), support vector regression (SVR), a multilayer-perceptron artificial neural network (MLP-ANN), and Gaussian process regression (GPR) algorithms, were used to predict the CS of FC. 261 experimental results were utilized, incorporating input variables such as density, water-to-cement ratio, and fine aggregate-to-cement ratio. …”

Estimating the refractive index of oxygenated and deoxygenated hemoglobin using genetic algorithm – support vector regression model by Alade, Ibrahim Olanrewaju, Bagudu, Aliyu, Oyehan, Tajudeen A., Abd Rahman, Mohd Amiruddin, Saleh, Tawfik A., Olatunjif, Sunday Olusanya

“…In this work, we proposed a very rapid and accurate computational intelligent approach using Genetic Algorithm/Support Vector Regression models to estimate the real part of the refractive index for oxygenated and deoxygenated hemoglobin samples. …”
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A hybrid genetic algorithm and linear regression for prediction of NOx emission in power generation plant by Bunyamin M.A., Yap K.S., Aziz N.L.A.A., Tiong S.K., Wong S.Y., Kamal M.F.

“…This paper presents a new approach of gas emission estimation in power generation plant using a hybrid Genetic Algorithm (GA) and Linear Regression (LR) (denoted as GA-LR). …”

Depth Map Estimation based on Linear Regression using Image Focus by Malik , Aamir Saeed, Song, Taek Lyul, Choi, Tae-Sun

“…This paper presents a method for depth estimation using image focus based on the linear regression model. …”
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Outlier detection in circular regression model using minimum spanning tree method by Nur Faraidah, Muhammad Di, Siti Zanariah, Satari, Roslinazairimah, Zakaria

“…Then, the performances of both algorithms were measured using “success” probability. …”
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Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

“…The multi-class classification strategy is used to ensure quick estimation of the multi-class NN algorithms. …”
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Robust multivariate least angle regression by Uraibi, Hassan Sami, Midi, Habshah, Rana, Sohel

“…The least angle regression selection (LARS) algorithms that use the classical sample means, variances, and correlations between the original variables are very sensitive to the presence of outliers and other contamination. …”
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Detection of multiple outliners in linear regression using nonparametric methods by Adnan, Robiah

“…New Algorithms for Computing the Least Trimmed Squares Regression Estimator. …”
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Rank regression for modeling bus dwell time in the presence of censored observations by Karimi, Mostafa, Ibrahim, Noor Akma

“…A resampling technique is used for estimating the distribution of the rank estimator through its empirical distribution. …”
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Advanced flood prediction at forest with rainfall data using various machine learning algorithms by M.S., Saravanan, S., Sivashankar, A., Rajesh, Mat Ibrahim, Masrullizam

“…The aim is to classify and predict floods in advance with rain data patterns of India using spatio-temporal logic. Two Classification algorithms are used to achieve the maximum accuracy namely K-Nearest Neighbour with a sample size=5 and Logistic Regression with a sample size=5 for continues iterations. …”
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Multiple equations model selection algorithm with iterative estimation method by Kamarudin, Nur Azulia, Ismail, Suzilah

“…There have been various procedures suggested to date, whether through manual or automated selections, to choose the best model.This study nonetheless focuses on an automated selection for multiple equations model with the use of iterative estimation method. In particular, an algorithm on model selection for seemingly unrelated regression equations model using iterative feasible generalized least squares estimation method is proposed. …”
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LASSO-type estimations for threshold autoregressive and heteroscedastic time series models. by Muhammad Jaffri Mohd Nasir

“…Empirical studies using these univariate and multivariate models show that the BCD algorithms estimate less irrelevant thresholds compared to the approximation group LASSO algorithms of group least angle regression (GLAR). …”
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Robust techniques for linear regression with multicollinearity and outliers by Mohammed, Mohammed Abdulhussein

“…The MM-estimator and the MGM-estimator are integrated in the JRR algorithm for the establishment of the improved versions of JRR. …”
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