Search Results - (( variable regression detection algorithm ) OR ( evolution optimization mining algorithm ))
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1
Y-type Random 2-satisfiability In Discrete Hopfield Neural Network
Published 2024“…During the retrieval phase, a new activation function and Swarm Mutation were proposed to ensure the diversity of the neuron states. The proposed algorithm and mutation mechanism showed optimal performances as compared to the existing algorithms. …”
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2
Logic mining method via hybrid discrete hopfield neural network
Published 2025“…The first contribution involves the incorporation of a Hybrid Differential Evolution Algorithm to accelerate the optimization of synaptic weights during the training phase. …”
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…A new self-adaptive hybrid algorithm (CSCMAES) is introduced for optimization. …”
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Seed disperser ant algorithm for optimization / Chang Wen Liang
Published 2018“…The Seed Disperser Ant Algorithm (SDAA) is developed based on the evolution or expansion process of Seed Disperser Ant (Aphaenogaster senilis) colony. …”
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5
Classification with degree of importance of attributes for stock market data mining
Published 2004“…The experimental results show that predictive FDT algorithm can generate a relatively optimal tree without much computation effort (comprehensibility), and WFPRs have a better predictive accuracy of stock market time series data. …”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…Lastly, we consider the problem of detecting multiple outliers in circular regression models based on the clustering algorithm. …”
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7
Detection of energy theft and defective smart meters in smart grids using linear regression
Published 2017“…In this paper, we design two linear regression-based algorithms to study consumers’ energy utilization behavior and evaluate their anomaly coefficients so as to combat energy theft caused by meter tampering and detect defective smart meters. …”
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8
Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification
Published 2011“…A deterministic mutation-based algorithm is introduced to overcome this problem. Identification studies using NARX (Nonlinear AutoRegressive with eXogenous input) models employing simulated systems and real plant data are used to demonstrate that the algorithm is able to detect significant variables and terms faster and to select a simpler model structure than other well-known EC methods.…”
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Descriptive analysis of patient diet trends at Pantai Hospital Ayer Keroh
Published 2025“…Without effective data analysis, it is challenging to track dietary trends, assess patient preferences, and optimize meal preparation. To address this problem, this project focuses on enhancing various aspects of healthcare dietary operations by employing CRISP-DM as the methodology to structure the data mining process. …”
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11
A novel ensemble decision tree-based CHi-squared Automatic Interaction Detection (CHAID) and multivariate logistic regression models in landslide susceptibility mapping
Published 2014“…An ensemble algorithm of data mining decision tree (DT)-based CHi-squared Automatic Interaction Detection (CHAID) is widely used for prediction analysis in variety of applications. …”
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Crack damage detection of reinforced concrete beams using local stiffness indicator
Published 2011“…The mode shape equation for the beams was obtained by using nonlinear regression. Global flexural stiffness was derived by utilizing the regressed variable into the equation for transverse vibration of a Bernoulli-Euler prismatic beam. …”
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Robust Estimation Methods And Outlier Detection In Mediation Models
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14
Panel regression method to analyse the stock market returns due to Covid-19 / Nur Mardziah Aziz Jaafar and Noraini Noordin
Published 2021“…This study aimed to determine the aftereffects of COVID-19 pandemic outbreaks on stock markets by measuring the correlation between market returns and daily growth of total new and death cases of COVID-19. Panel regression methods, namely pooled ordinary least square and fixed-effect methods were used in this study where the dependent variable is stock market returns and independent variables were i) daily growth new death cases COVID-19 ii) natural algorithm market capitalisation iii) Brent Crude Oil Price from January 2, 2020, until March 31, 2020. …”
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Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration
Published 2014“…The main objective of this article is to use CHi-squared automatic interaction detection (CHAID) method to perform the best classification fit for each conditioning factor, then, combining it with logistic regression (LR). …”
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Chemometrics analysis for the detection of dental caries via ultraviolet absorption spectroscopy / Katrul Nadia Basri
Published 2023“…Dimension reduction algorithm such as LDA and CNN were applied on the spectra to reduce the number of variables to be trained. …”
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17
Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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LED based NIR spectroscopy for detection of lard adulteration in palm oil via chemometrics / Katrul Nadia Basri
Published 2017“…In order to remove the uninformative variables, cumulative adaptive reweighted sampling (CARS) has been performed. …”
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FT-NIR, MicroNIR and LED-MicroNIR for detection of adulteration in palm oil via PLS and LDA
Published 2018“…Quantitative analysis was performed using partial least square (PLS) algorithms with the linear regression method. The best correlation coefficient, (R2), reported using FT-NIR was 0.99 with RMSEC and RMSEP values less than 1, indicating that the spread of calibration and prediction data was small. …”
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On line fault detection for transmission line using power system stabilizer signals
Published 2007“…Hence, this study will show that not only the PSS able to compensate the damping due to the disturbance but also by using the developed algorithm it succeeds to detect and classify the fault conditions on the parallel transmission lines.…”
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