Search Results - ((linear algorithm) OR (mining algorithm))

Utilisation of Exponential-Based Resource Allocation and Competition in Artificial Immune Recognition System by Hormozi, Shahram Golzari

“…Artificial Immune Recognition System is one of the several immune inspired algorithms that can be used to perform classification, a data mining task. …”
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A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani by Mahmoud Reza, Saybani

“…The components of the AIRS2 algorithm that pose problems will be modified. This thesis proposes three new hybrid algorithms: The FRA-AIRS2 algorithm uses fuzzy logic to improve data reduction capability of AIRS2 and to solve the linearity problem associated with resource allocation of AIRS. …”
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Dissimilarity algorithm on conceptual graphs to mine text outliers by Kamaruddin, Siti Sakira, Hamdan, Abdul Razak, Abu Bakar, Azuraliza, Mat Nor, Fauzias

“…In Comparison to other text outlier detection method, this approach managed to capture the semantics of documents through the use of CGs and is convenient to detect outliers through a simple dissimilarity function.Furthermore, our proposed algorithm retains a linear complexity with the increasing number of CGs.…”
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Prediction Of Leaf Mechanical Properties Based On Geometry Features With Data Mining by H’ng, Choo Wooi

“…The linear models and rules developed from the M5P algorithm were adopted for the FT indicator prediction modelling of 14 attributes. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

“…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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A new model for iris data set classification based on linear support vector machine parameter's optimization by Faiz Hussain, Zahraa, Ibraheem, Hind Raad, Alsajri, Mohammad, Ali, Ahmed Hussein, Mohd Arfian, Ismail, Shahreen, Kasim, Sutikno, Tole

“…The SVM is a one technique of machine learning techniques that is well known technique, learning with supervised and have been applied perfectly to a vary problems of: regression, classification, and clustering in diverse domains such as gene expression, web text mining. In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction.…”
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Sustainable energy management: Artificial intelligence-based electricity consumption prediction in limited dataset environment for industry applications by Chuan, Zun Liang, Tan, Lit Ken, Wee, Angel Chi Chyin, Yim Hin, Tham, Shao, Jie Ong, Jia, Yi Low, Chong, Yeh Sai

“…This study aimed to develop a modified stacked ensemble multivariable Artificial Intelligence (AI)-based predictive algorithm, specifically Stacked Simple Linear Regression and Multiple Linear Regression (SLR-MLR), and Stacked Simple Linear Regression and Multiple Non-Linear Regression (SLR-MNLR) utilizing the Cross Industry Standard Process for Data Mining (CRISP-DM) data science methodology. …”
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Enhancing electricity consumption forecasting in limited dataset: A simple stacked ensemble approach incorporating simple linear and support vector regression for Malaysia by Chuan, Zun Liang, Shao Jie, Ong, Yim Hin, Tham, Siti Nur Syamimi, Mat Zain, Yunalis Amani, Abdul Rashid, Ainur Naseiha, Kamarudin

“…This article introduces a novel artificial intelligence (AI) time-series algorithm, a simple stacked ensemble of simple linear regression (SLR) and Support Vector Regression (SVR), designed to forecast Malaysia’s annual electricity consumption, particularly in scenarios with limited datasets utilizing the Cross Industry Standard Process for Data Mining (CRISP-DM) data science methodology. …”
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An improvement algoithm for Iris classification by using Linear Support Vector Machine (LSVM), k-Nearest Neighbours (k-NN) and Random Nearest Neighbous (RNN) / Ahmad Haadzal Kamar... by Kamarulzalis, Ahmad Haadzal, Abdullah, Mohd Asrul Affendi

“…Aims of this study is to improve an existing algorithm technique for classification. The ideas come from a combination of k-NN algorithm and ensemble concept. …”
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An accurate algorithm of numerical integration for computing seismic responses of inelastic structures by Miyahara, Masato, Ijima, Katsushi, Obiya, Hiroyuki, Zakaria, Muhammad Nizam bin

“…These numerical integrations, however, give exacter results in linear seismic responses than that by the numerical integrations without any conditions. …”
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Evaluating integrated weight linear method to class imbalanced learning in video data by Mohd Apandi, Ziti Fariha, Mustapha, Norwati, Affendey, Lilly Suriani

“…This paper proposed an Integrated Weight Linear (IWL) method that integrate weight linear algorithm (WL) with principle component analysis (PCA) to eliminate imbalanced dataset in soccer video data. …”
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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.

Subjects:

Logistic regression methods for classification of imbalanced data sets by Santi Puteri Rahayu, -

“…This thesis aims to develop the simple and effective imbalanced classification algorithms by previously improving the algorithms performance of general classifiers i.e. …”
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Hybridization of Ensemble Kalman Filter and Non-linear Auto-regressive Neural Network for Financial Forecasting by Lai, Fong Woon

“…In this study, a novel hybrid model, called UKF-NARX, consists of unscented kalman filter and non-linear auto-regressive network with exogenous input trained with bayesian regulation algorithm is modelled for chaotic financial forecasting. …”
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Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

“…Many attempts have been made for meaningful prediction from real time stock market data by using data mining and statistical techniques such as Support Vector Machine [1,2], and Linear and Non- Linear Statistical Models [3,4], Neural Networks [5, 6]. …”
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Sentiment analysis on national cultural tourism using Linear Support Vector Machine (LSVM) / Nur Haida Hanna Samsuddin by Samsuddin, Nur Haida Hanna

“…Therefore, the chosen technique is classification and the algorithm that will be applied in the classification process is Linear Support Vector Machines (LSVM). …”
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Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman by Seman, Ali

“…In addition, the algorithm was also efficient in terms of time complexity which was recorded as O (km(n-k) and considered as linear. …”
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ANALYSIS OF STOCK PRICE PREDICTION USING DATA MINING APPROACH by Mukhariz bin Muhamad, Mukhariz

“…Using Data Mining approach in training the algorithms that will produce the best results based on Public Listed Companies‟ stock price data that dates back until 1998. …”
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Hybridization of Ensemble Kalman Filter and Non-linear Auto-regressive Neural Network for Financial Forecasting by Said , Jadid Abdulkadir, Suet Peng, Yong, Maran , Marimuthu, Lai, Fong Woon

“…In this study, a novel hybrid model, called UKF-NARX, consists of unscented kalman filter and non-linear auto-regressive network with exogenous input trained with bayesian regulation algorithm is modelled for chaotic financial forecasting. …”
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Hybridization of Ensemble Kalman Filter and Non-linear Auto-regressive Neural Network for Financial Forecasting by Said, Jadid Abdulkadir, Yong, S.P., Maran, Marimuthu, Lai, Fong Woon

“…In this study, a novel hybrid model, called UKF-NARX, consists of unscented kalman filter and non-linear auto-regressive network with exogenous input trained with bayesian regulation algorithm is modelled for chaotic financial forecasting. …”
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