Search Results - (( data selection method algorithm ) OR ( re evaluation method algorithm ))
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Hybrid metaheuristic method for clustering in wireless sensor networks / Bryan Raj Peter Jabaraj
Published 2023“…As such, this thesis proposes a hybrid metaheuristic method that consists of Sperm Swarm Optimization (SSO) algorithm and Genetic Algorithm (GA), which is termed HSSOGA. …”
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Thesis -
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A regression test case selection and prioritization for object-oriented programs using dependency graph and genetic algorithm
Published 2014“…The goal is to identify changes in a method's body due to data dependence, control dependence and dependent due to object relation such as inheritance and polymorphism, select the test cases based on affected statements and ordered them based on their fitness by using GA. …”
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Energy, Vibration And Sound Research Group (e-VIBS) School Of Science And Technology Universiti Malaysia Sabah : Bioacoustics Signal Modeling Using Time-Frequency Distribution
Published 2011“…However, WSE was the best method for the RE approach with the accuracy of 92%. …”
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Research Report -
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State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model
Published 2023“…In the first stage, the model is pre-trained using unlabeled data with unsupervised learning. In the second stage, the model is fine-tuned or re-trained using labeled data with supervised learning. …”
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Segmentation of MRI brain images using statistical approaches
Published 2011“…The non-Local means (NL-means) algorithm is a state-of-the art neighbourhood-based noisereduction method which is time-consuming and its accuracy can be improved. …”
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Multiple equations model selection algorithm with iterative estimation method
Published 2016“…Meanwhile, real data analysis using water quality index displays excellent accomplishments when compared to other selection procedures.Consequently, iterative feasible generalized least squares method is regarded as a more suitable estimation method in this automated selection.It can also be seen that simultaneous selections outperform the individual selections.This strategy by executing simultaneous selection with iterative estimation method is therefore proven to outclass in this analysis.…”
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Application of the bees algorithm to the selection features for manufacturing data
Published 2007“…Some of the features may contain irrelevant information caused by data redundancy or by noise. A “wrapper” feature selection method using the Bees Algorithm and Multilayer Perception (MLP) networks is described in this paper. …”
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Conference or Workshop Item -
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Case Slicing Technique for Feature Selection
Published 2004“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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Removal of heavy metals from water by functionalized carbon nanotubes with deep eutectic solvents: An artificial neural network approach / Seef Saadi Fiyadh
Published 2019“…The best result achieved for Pb2+ removal using ANFIS algorithm is with RE 7.078%. For As3+ removal using different adsorbents, two algorithms were applied for the modelling, the feed-forward back-propagation maximum RE achieved is 5.97% while, the NARX algorithm achieved better accuracy with maximum RE of 5.79%. …”
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A hybrid grey wolf assisted-sparrow search algorithm for frequency control of RE integrated system
Published 2023“…Moreover, the robustness of the proffered method is also evaluated under the random varying load, variation of HPS system parameter, and weather intermittency of RE resources in real-time conditions. …”
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Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…Results of the reviewed techniques show that attribute selection methods capable to resolve the limitations in ID3 algorithm and increase the performance of the method. …”
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi
Published 2019“…Experiments demonstrate and prove that the proposed EBPSO method produces better accuracy mining data and selecting subset of relevant features comparing other algorithms. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…Experiments demonstrate that ensemble classifier learning method produces better accuracy mining data streams and selecting subset of relevant features comparing other single classifiers. …”
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Sentiment classification for malay newspaper using clonal selection algorithm / Nur Fitri Nabila Mohamad Nasir
Published 2013“…The experimental results show that our method can achieve better performance in clonal selection algorithm sentiment classification and the data collected cannot be used at once in this model because training data is very time-consuming if using all the data. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…In cluster generating process, the developed BBSI algorithm was used to select the best band combination for generating cluster by using Iterative self- Organizing Data Analysis (ISODATA) technique. …”
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A partition based feature selection approach for mixed data clustering / Ashish Dutt
Published 2020“…One such pre-processing algorithm in EDM is clustering. It is a widely used method in data mining to discover unique patterns in underlying data. …”
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Performance comparison of feature selection methods for prediction in medical data
Published 2023“…This study analyzes filter, wrapper, and embedded feature selection methods for medical data with the predictive machine learn- ing algorithm, Random Forest and CatBoost. …”
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Proceeding Paper -
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AGENT MEETING SCHEDULER
Published 2011“…An agent meeting scheduler prototype then will be developed to prove that the selected algorithm is working properly. Qualitative research method is being used to gather necessary data on agent algorithm and this data will be used to select the suitable algorithm. …”
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Final Year Project
