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1
Improving ant swarm optimization with embedded vaccination for optimum reducts generation
Published 2013“…This paper proposes a hybrid ant swarm optimization algorithm by using immunity to discover better fitness value in optimizing rough reducts set. …”
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An improved genetic-fuzzy system for classification and data analysis
Published 2017“…Interpretability of classification systems, which refers to the ability of these systems to express their behavior in an understandable way, has recently gained more attention and it is considered as an important requirement especially for knowledge-based systems. …”
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Stage of maturity banana fruit classification using image processing / Nadia Kasim ... [et al.]
Published 2019Subjects: “…Analytical methods used in the solution of physical problems…”
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4
Underwater Image Recognition using Machine Learning
Published 2024“…Machine Learning is the branch of Artificial Intelligence in which a computer is fed with data and based on that data it tries to find out solution on its own. It encompasses the procedure for feeding algorithms information to create the algorithms realize patterns in the data and then increase the performance of the algorithms. …”
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Evolutionary Fuzzy ARTMAP Neural Networks for Classification of Semiconductor Defects
Published 2014“…Wafer defect detection using an intelligent system is an approach of quality improvement in semiconductor manufacturing that aims to enhance its process stability, increase production capacity, and improve yields. …”
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Footwear quality evaluation using decision tree and logistic regression models
Published 2022“…The objectives of the study are to determine the rank factors that affect the quality of footwear using decision tree methods. Then, various types of decision trees and logistic regression model are developed to gain the best classification model for predicting footwear quality performance. …”
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Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying
Published 2019“…An ensemble of these algorithms is an intelligent and adaptive solution, producing a clean output, while preserving significant pixel information. …”
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8
Problem restructuring in interger programming for reduct searching
Published 2003“…These reducts are the minimal attributes of the information system that are useful in classificatory task. They can describe the whole information system when implementing discernment. …”
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9
Near-infrared technique for oil palm fruit grading system
Published 2013“…The grading systems in general utilized improved engineering designs with image processing techniques to ensure the quality of the product.In this research, a hyperspectral oil palm grading system was built and an image processing techniques algorithm was developed based on the spectral reflectance of the external features of oil palm fresh fruit bunches (FFB). …”
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10
Real-time oil palm fruit bunch ripeness grading system using image processing techniques
Published 2013“…This system will be useful to the oil palm plantations in Malaysia and the rest of the oil-palm growing world. …”
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Performance of Levenberg-Marquardt neural network algorithm in power quality disturbances classification / Adibah I’zzah Mohamad Kasim
Published 2025“…The increasing complexity of modern power systems necessitates advanced methods for detecting and classifying power quality disturbances (PQDs), which impact system reliability and equipment performance. …”
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12
Development Of An Intelligent System For River Water Quality Classification Based On Algae Composition
Published 2006“…In this study, an intelligent system is developed for the classification of river water quality using the HMLP network. …”
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Monograph -
13
A speech enhancement framework using discrete Krawtchouk-Tchebichef Transform
Published 2018“…Therefore, robust Speech Enhancement Algorithms (SEA) that suppress noise without distorting the original signals are necessary. …”
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14
A comparative study between rough and decision tree classifiers
Published 2008“…Theoretically, a good set of knowledge should provide good accuracy when dealing with new cases.Besides accuracy, a good rule set must also has a minimum number of rules and each rule should be short as possible.It is often that a rule set contains smaller quantity of rules but they usually have more conditions.An ideal model should be able to produces fewer, shorter rule and classify new data with good accuracy.Consequently, the quality and compact knowledge will contribute manager with a good decision model.Because of that, the search for appropriate data mining approach which can provide quality knowledge is important.Rough classifier (RC) and decision tree classifier (DTC) are categorized as RBC.The purpose of this study is to investigate the capability of RC and DTC in generating quality knowledge which leads to the good accuracy.To achieve that, both classifiers are compared based on four measurements that are accuracy of the classification, the number of rule, the length of rule, and the coverage of rule.Five dataset from UCI Machine Learning namely United States Congressional Voting Records, Credit Approval, Wisconsin Diagnostic Breast Cancer, Pima Indians Diabetes Database, and Vehicle Silhouettes are chosen as data experiment.All datasets were mined using RC toolkit namely ROSETTA while C4.5 algorithm in WEKA application was chosen as DTC rule generator.The experimental results indicated that both classifiers produced good classification result and had generated quality rule in different types of model – higher accuracy, fewer rule, shorter rule, and higher coverage.In term of accuracy, RC obtained higher accuracy in average while DTC significantly generated lower number of rule than RC.In term of rule length, RC produced compact and shorter rule than DTC and the length is not significantly different.Meanwhile, RC has better coverage than DTC.Final conclusion can be decided as follows “If the user interested at a variety of rule pattern with a good accuracy and the number of rule is not important, RC is the best solution whereas if the user looks for fewer nr, DTC might be the best choice”…”
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Monograph -
15
Intent-IQ: customer’s reviews intent recognition using random forest algorithm
Published 2025“…Therefore, the RF classification model is chosen to be integrated into the Intent-IQ system. …”
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A novelty classification model for varied agarwood oil quality using the K-Nearest Neighbor algorithm / Aqib Fawwaz Mohd Amidon … [et al.]
Published 2022“…As a result, a new grading system based on artificial algorithms, namely K-Nearest Neighbor algorithms, was established. …”
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Book Section -
17
A De-noising Scheme for Wavelet Based Power Quality Disturbances Detection and Classification system
Published 2011“…Using the de-noising scheme proposed in this paper, a higher tolerance to noise can be achieved by the Power Quality Problem Classification system.…”
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A De-noising Scheme for Enhancing Power Quality Problem Classification System Based on Wavelet Transform and Rule-Based Method
Published 2011“…Using the de-noising scheme proposed in this paper, a higher tolerance to noise can be achieved by the Power Quality Problem Classification system.…”
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Real-time power quality disturbance classification using convolutional neural networks
Published 2020“…There is a growing interest in disturbance monitoring to maintain power quality. This paper developed a real-time power quality disturbance (PQD) detection system using convolutional neural networks (CNN) due to its fast and accurate feature extraction and classification. …”
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