Search Results - (( panel estimation method algorithm ) OR ( data normalization based algorithm ))
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Robust estimation methods for fixed effect panel data model having block-concentrated outliers
Published 2019“…The Ordinary Least Squares (OLS) is the commonly used method to estimate the parameters of fixed effect panel data model. …”
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Thesis -
2
Estimating Crack Effects on Electrical Characteristics of PV Modules Based on Monitoring Data and I-V Curves
Published 2024“…Meanwhile, an innovative parameter optimization algorithm based on particle swarm optimization is developed to extract the parameters. …”
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Implementation of a modified incremental conductance MPPT algorithm with direct control based on a fuzzy duty cycle change estimator using dSPACE
Published 2014“…A controlled Cuk DC-DC converter was implemented and connected to a SunTech STP085B PV panel to verify the accuracy of the proposed method. …”
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Performance analyses of various photovoltaic power plant based on local spectral irradiances in Malaysia using genetic algorithm
Published 2023“…Besides, the genetic algorithm has showed that it is an effective and efficient way to perform estimation of optimal tilt angle and orientation angle for solar sites with genetic algorithm as it is able to produce correct and accurate result in a short amount of time.…”
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Final Year Project / Dissertation / Thesis -
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Modeling and analysis of the impact of information and communication technology on household consumption expenditure in different regions
Published 2022“…Based on the panel data of cities and towns in China, by using the generalized estimation method of a dynamic panel, through the construction of regional household consumption expenditure evaluation models, optimize the impact evaluation algorithm of household consumption expenditure in different regions, standardize critic indicators, and build the impact modeling of household consumption expenditure in combination with relevant algorithms such as the Engel coefficient. …”
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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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Thesis -
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Classification of Cardiac Disorders Based on Electrocardiogram Data with Fuzzy Cognitive Map (FCM) Algorithm Approach
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Conference or Workshop Item -
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The effect of dose calculation algorithms on the normal tissue complication probability values of thoracic cancer
Published 2015“…Purpose: To identify the effect of dose calculation algorithms on the Normal Tissue Complication Probability values of thoracic cancer. …”
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Monograph -
10
A study on advanced statistical analysis for network anomaly detection
Published 2005“…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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Monograph -
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Data normalization techniques in swarm-based forecasting models for energy commodity spot price
Published 2014“…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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Conference or Workshop Item -
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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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Thesis -
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…Even a normal people using clustering to grouping their data. …”
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14
An improved recommender system based on normalization of matrix factorization and collaborative filtering algorithms
Published 2015“…The hypothesis is that the tendency of normalization technique to simplify the data combined with the accuracy of the neighborhood models can improve the accuracy of the RS. …”
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Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream
Published 2023“…Existing clustering algorithms for outlier detection encounter significant challenges due to insufficient data pre-processing methods and the absence of a suitable data summarization framework for effective data stream clustering. …”
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Thesis -
18
Pengkelasan Sel Kanser Pangkal Rahim Kepada Sel Normal Dan Tidak Normal Menggunakan Analisis Pembezalayan Dan Rangkaian Neural
Published 2006“…The system is built to classify some certain data into two classes, which are normal or abnormal cells. …”
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Monograph -
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A clustering-based method for outlier detection under concept drift
Published 2024“…However, challenges may arise from assuming the majority of data comprises normal instances, particularly during sudden spikes in attack data, potentially diminishing algorithm effectiveness. …”
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