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Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…Unlike the classical kNN algorithm which is a regression type algorithm, the proposed localisation algorithms utilise machine learning classification for both linear and kernel types. …”
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A novel islanding detection technique using modified Slantlet transform in multi-distributed generation
Published 2019“…A Harmony Search Algorithm (HSA) is used to optimally specify suitable scales of Slantlet transform and Slantlet decomposition levels for accurate islanding classification. …”
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…In this paper, an improved intrusion detection algorithm for multiclass classification was presented and discussed in detail. …”
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Development of cost reduction mathematical model for natural gas transmission network system
Published 2012“…Therefore, a new classification proposed on the natural gas networks from the oil and gas wells to the consumers. …”
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023Subjects:Conference Paper -
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An accurate infant cry classification system based on continuos hidden Markov model
Published 2023Subjects:Conference Paper -
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Adaptive parameter control strategy for ant-miner classification algorithm
Published 2020“…This paper presents a new hybrid Ant-Miner classification algorithm and ant colony system (ACS), called ACS-Ant Miner. …”
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Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification
Published 2023“…FESSIC outperforms other algorithms for average classification accuracy for the KSVM, MLP, RF and DT classifiers. …”
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Fuzzy modeling using Bat Algorithm optimization for classification
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Undergraduates Project Papers -
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A speech enhancement framework using discrete Krawtchouk-Tchebichef Transform
Published 2018“…For Speech-Shaped noise, the improvements are 0.23 (11.3%), 0.17 (9.1%), 2.05 (31.6%), and 0.05 (7.8%), respectively. Moreover, the classification accuracy has been reached to 99.44%. This work contributed in developing a new transform, finding a new speech and noise models, introducing new linear and non-linear estimators with their adaptively smoothing parameter to get good noise reduction. …”
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Improvement of fuzzy neural network using mine blast algorithm for classification of Malaysian Small Medium Enterprises based on strength
Published 2015“…Many researchers have trained ANFIS parameters using metaheuristic algorithms but very few have considered optimizing the ANFIS rule-base. …”
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Affect classification using genetic-optimized ensembles of fuzzy ARTMAPs
Published 2015“…In addition, manual design of classification tasks often uses sub-optimum classifier parameter settings, leading to average classification performance. …”
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An Ar Natural Marker Similarities Measurement Algorithm For E-Biodiversity
Published 2018“…The objective of this research is to comparatively evaluate the effectiveness of different algorithms, method combination procedure, and their parameters towards classification accuracy. …”
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Proceeding -
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Development of an intelligent prediction tool for rice yield based on machine learning techniques
Published 2006“…Support vector machine algorithm is developed for classification of rice plantation data. …”
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Using the bees algorithm to optimise a support vector machine for wood defect classification
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Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah
Published 2021“…To improve the performance from current systems, this work has investigation on different of image pre-processing enhancement technique to support accuracy on deep learning for DR classification. …”
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