Search Results - (( generation classification model algorithm ) OR ( code classification methods algorithm ))
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Blood cell classification using deep learning
Published 2022“…The sole objective of the continuation of this project II is to define an efficient WBC classification model from scratch. The motivation was gotten from the literature review section where various researchers developed their own methods manually through experimenting such as ensemble methods, learning algorithms, combined methodologies, etc. …”
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Final Year Project / Dissertation / Thesis -
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POWER QUALITY CLASSIFICATION WITH DE-NOISING SCHEME USING WAVELET TRANSFORM AND RULE- BASED METHOD
Published 2012“…Simulation produces satisfactory result in identifying the disturbance and proves that it is possible to use this model for power disturbance classification even in a noisy environment. …”
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Using genetic algorithms to optimise land use suitability
Published 2012“…In this study, under environmentfriendliness objective, based on multi-agent genetic algorithms, was developed a geospatial model for the land use allocation. …”
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Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization
Published 2014“…In this method, features were extracted from Android applications byte-code through static code analysis, selected and were used to train supervised classifiers. …”
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Proceeding Paper -
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Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization
Published 2015“…In this method, permission-based features were extracted from Android applications byte-code through static code analysis, selected and were used to train supervised classifiers. …”
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Article -
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New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…The accuracy of the classification rules by the proposed models was high compared to other models.…”
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Development of classification algorithms of human gait
Published 2022“…In addtion, after compared with other state-of-the-arts of gait classification algorithms, our proposed classification algorithm produced comparable results with other state-of-arts using a smaller dataset with fewer training features.…”
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Final Year Project / Dissertation / Thesis -
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Next generation insect taxonomic classification by comparing different deep learning algorithms
Published 2022“…The results show that different taxonomic ranks require different deep learning (DL) algorithms to generate high-performance models, which indicates that the design of an automated systematic classification pipeline requires the integration of different algorithms. …”
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Article -
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Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…In order to solve it, Bat Algorithm method is implement in to optimization method in fuzzy modeling for classification. …”
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Undergraduates Project Papers -
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…These rules consist of conditions over attribute value pairs called the descriptions, and decision attributes. Therefore generating a good decision model or classification model is a major component in many data mining researches. …”
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Chain coding and pre processing stages of handwritten character image file
Published 2010“…Each of the pre-processing stages and the chain coding process will be described in detail giving improvised algorithms, and examples of the processes on existing samples from the database shown. …”
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Article -
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Modified word representation vector based scalar weight for contextual text classification
Published 2024“…Based on the acquired results, the experiments reveal that the modified word vectors algorithm can effectively alter original LLM-generated word vectors to reflect intended contexts and can outperform baseline scores in contextual text classification tasks. …”
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Building classification models from imbalanced fraud detection data / Terence Yong Koon Beh, Swee Chuan Tan and Hwee Theng Yeo
Published 2014“…When the data is imbalanced, these algorithms generate models that achieve good classification accuracy for the majority class, but poor accuracy for the minority class. …”
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Article -
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IP algorithms in compact rough classification modeling
Published 2001“…The paper presents the Integer Programming (IP) algorithms in mining a compact rough classification model. …”
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Accuracy assessment of Digital Terrain Model (DTM) Constructed Cloth Simulation Filter (CSF) and Multi Curvature Classification (MCC) algorithm on UAV LiDAR dataset / Mohamad Khair...
Published 2023“…This study aims to evaluate the effectiveness of open-source software algorithms for ground classification in lidar point clouds and the subsequent generation of accurate DTMs. …”
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Student Project -
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A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules
Published 2013“…Thus, a higher predictive power classification model for various fields could be generated.…”
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Thesis -
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Ideal combination feature selection model for classification problem based on bio-inspired approach
Published 2020“…Experimental results revealed that the ideal combination is a feature selection model with the implementation of bio-inspired search algorithm that consistently obtains the optimal solution (i.e. less number of features with higher classification accuracy) on the selected dataset. …”
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Book Section -
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An extended oversampling method for imbalanced Quranic text classification based on a genetic algorithm
Published 2023“…The results of the study demonstrate the effectiveness of the Genetic algorithm in generating a balanced dataset, which leads to better classification performance results. …”
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Article -
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A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition
Published 2002“…In this thesis rough sets approach was used in the preprocessing stages, namely in the vector quantization operation in which feature vectors are quantized or classified to a finite set of codebook classes. Classification rules were generated from training feature vectors set, and a modified form of the standard voter classification algorithm, that use the rough sets generated rules, was applied. …”
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