Search Results - (( java application using algorithm ) OR ( (variable OR variables) regression based algorithm ))

Automated time series forecasting by Ismail, Suzilah, Zakaria, Rohaiza, Tuan Muda, Tuan Zalizam

“…Moving Average, Decomposition, Exponential Smoothing, Time Series Regressions and ARIMA) were used.The algorithm was developed in JAVA using up to date forecasting process such as data partition, several error measures and rolling process.Successfully, the results of the algorithm tally with the results of SPSS and Excel.This automatic forecasting will not just benefit forecaster but also end users who do not have in depth knowledge about forecasting techniques.…”
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Enhancing Model Selection Based On Penalized Regression Methods And Empirical Mode Decomposition by Al Jawarneh, Abdullah Suleiman Saleh

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Penalized Quantile Regression Methods And Empirical Mode Decomposition For Improving The Accuracy Of The Model Selection by Ambark, Ali Saleh Al-Massri

“…Therefore, three methods based on a combination of the empirical mode decomposition (EMD) algorithm and penalized quantile regression have been proposed in this study. …”
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The performance of Taguchi�s T-method with binary bat algorithm based on great value priority binarization for prediction by Marlan Z.M., Ramlie F., Jamaludin K.R., Harudin N.

“…This paper proposes an optimization algorithm based on the Binary Bat algorithm methodology for replacing the conventional orthogonal array approach. …”

Bayesian logistic regression model on risk factors of type 2 diabetes mellitus by Chiaka, Emenyonu Sandra

“…Logistic regression model has long been known and it is commonly used in analysing a binary outcome or dependent variable and connects the binary dependent variable to several independent variables. …”
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Weather prediction in Kota Kinabalu using linear regressions with multiple variables by Teong, Khan Vun, Chung, Gwo Chin, Jedol Dayou

“…Numerical weather prediction is the process of using existing numerical data on weather conditions to forecast the weather using machine learning algorithms. This study employs machine learning algorithms, a linear regression model using statistics, and two optimization approaches, the normal equation approach, and gradient descent approach to predict the weather based on a few variables. …”
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Feasibility analysis for predicting the compressive and tensile strength of concrete using machine learning algorithms by Ziyad Sami B.H., Ziyad Sami B.F., Kumar P., Ahmed A.N., Amieghemen G.E., Sherif M.M., El-Shafie A.

“…Also, the model performance was characterized based on the number of input variables utilized. …”

Comparison of Conjugate Gradient methods for developing the multiple linear regression model for rubber yield in Malaysia / Anis Shahida Rohimi Ozeman by Rohimi Ozeman, Anis Shahida

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Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers by Uraibi, Hassan S.

“…We develop Robust Forward Selection algorithm based on RFCH correlation coefficient (RFS.RFCH) because FS.Winso is not robust to multivariate outliers. …”
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Enhancing riverine load prediction of anthropogenic pollutants: Harnessing the potential of feed-forward backpropagation (FFBP) artificial neural network (ANN) models by Khairudin K., Ul-Saufie A.Z., Senin S.F., Zainudin Z., Rashid A.M., Abu Bakar N.F., Anas Abd Wahid M.Z., Azha S.F., Abd-Wahab F., Wang L., Sahar F.N., Osman M.S.

“…The considerable number of errors (with RMSE, MAE, and MRE) discovered in estimating riverine loads using the multiple linear regression (MLR) statistical model can be attributed to the nonlinear relationship between the independent variables (Q and Cx) and dependent variables (W). …”

Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification by Abd Samad, Md Fahmi

“…A deterministic mutation-based algorithm is introduced to overcome this problem. …”
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Independent And Dependent Job Scheduling Algorithms Based On Weighting Model For Grid Environment by M. Al-Najjar, Hazem

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Determination of tree stem volume : A case study of Cinnamomum by Noraini Abdullah

“…The three stem biomass equations adopted are namely, the Newton, Huber and Smalian’s formulae, based on the multiple regression (MR) and polynomial regression (PR) techniques. …”
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SURE-Autometrics algorithm for model selection in multiple equations by Norhayati, Yusof

“…Thus, this study aims to develop an algorithm for model selection in multiple equations focusing on seemingly unrelated regression equations (SURE) model. …”
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A machine learning approach of predicting high potential archers by means of physical fitness indicators by Muazu Musa, Rabiu, Abdul Majeed, Anwar P.P., Taha, Zahari, Chang, Siow Wee, Ab. Nasir, Ahmad Fakhri, Abdullah, Mohamad Razali

“…Hierarchical agglomerative cluster analysis (HACA) was used to cluster the archers based on the significant variables identified. k-NN model variations, i.e., fine, medium, coarse, cosine, cubic and weighted functions as well as logistic regression, were trained based on the significant performance variables. …”
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A machine learning approach of predicting high potential archers by means of physical fitness indicators by Musa, Rabiu Muazu, Anwar, P. P. Abdul Majeed, Zahari, Taha

“…Hierarchical agglomerative cluster analysis (HACA) was used to cluster the archers based on the significant variables identified. k-NN model variations, i.e., fine, medium, coarse, cosine, cubic and weighted functions as well as logistic regression, were trained based on the significant performance variables. …”
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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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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari by Satari, Siti Zanariah

“…Lastly, we consider the problem of detecting multiple outliers in circular regression models based on the clustering algorithm. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

“…The dissertation aims to develop an effectively decomposed time-series nongradient- based artificial intelligence model for forecasting a time-series regression machine learning task. …”
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