Search Results - (( evolution optimization method algorithm ) OR ( feature classification rules algorithm ))

Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

“…Feature selection was used to sort out key features for further classification. …”
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Ant colony optimization algorithm for rule based classification: Issues and potential by Al-Behadili, Hayder Naser Khraibet, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

“…This paper presents a review of related work of ACO rule classification which emphasizes the types of ACO algorithms and issues. …”
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Irrelevant feature and rule removal for structural associative classification by Mohd Shaharanee, Izwan Nizal, Jamil, Jastini

“…In the classification task, the presence of irrelevant features can significantly degrade the performance of classification algorithms,in terms of additional processing time, more complex models and the likelihood that the models have poor generalization power due to the over fitting problem.Practical applications of association rule mining often suffer from overwhelming number of rules that are generated, many of which are not interesting or not useful for the application in question.Removing rules comprised of irrelevant features can significantly improve the overall performance.In this paper, we explore and compare the use of a feature selection measure to filter out unnecessary and irrelevant features/attributes prior to association rules generation.The experiments are performed using a number of real-world datasets that represent diverse characteristics of data items.Empirical results confirm that by utilizing feature subset selection prior to association rule generation, a large number of rules with irrelevant features can be eliminated.More importantly, the results reveal that removing rules that hold irrelevant features improve the accuracy rate and capability to retain the rule coverage rate of structural associative association.…”
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A modified fuzzy min-max neural network with a genetic-algorithm-based rule extractor for pattern classification by Quteishat, A., Lim, C.P., Tan, K.S.

“…In this paper, a two-stage pattern classification and rule extraction system is proposed. …”
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Rule-based embedded HMMs phoneme classification to improve Qur’anic recitation recognition by Mohammed Ali Alqadasi, Ammar, Sunar, Mohd Shahrizal, Turaev, Sherzod, Abdulghafor, Rawad Abdulkhaleq Abdulmolla, Salam, Md Sah, Alashbi, Abdulaziz Ali Saleh, Ahmed Salem, Ali, Ali, Mohammed A. H.

“…This paper introduces a Rule-Based Phoneme Duration Algorithm to improve phoneme classification in Qur’anic recitation. …”
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An enhancement of classification technique based on rough set theory for intrusion detection system application by Noor Suhana, Sulaiman

“…In order to improve classification performance problem, feature selection and discretization algorithm are crucial in selecting relevant attributes that could improve classification performance. …”
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Development of fuzzy rule-based parameters for urban object-oriented classification using very high resolution imagery by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi

“…Supervised per-pixel classification algorithms including Maximum Likelihood and Support Vector Machine (SVM) were utilized to evaluate the capability of spectral-based classifiers to classify urban features. …”
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New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

“…Classification rules were generated based on the best reduct. …”
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A genetic algorithm based fuzzy inference system for pattern classification and rule extraction by Wong S.Y., Yap K.S., Li X.

“…However, in the event of having multiple variables coupled with a few features, the classification problem will be getting more sophisticated, as a result human expert may not be able to derive proper rules. …”

Genetic algorithm fuzzy logic for medical knowledge-based pattern classification by Tan, Chin Hooi, Tan, Mei Sze, Chang, Siow Wee, Yap, Keem Siah, Yap, Hwa Jen, Wong, Shen Yuong

“…GAFL possessed the advantage of fuzzy rules extraction feature apart from conventional classification technique compared to other models which are lack of fuzzy interpretation. …”
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Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

“…However, supervised learning technique has limitations for malware classification task. This paper presents a classification approach on android malware using candidate detectors generated from an unsupervised association rule of Apriori Algorithm. …”
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Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi

“…Many features were explored by using a DM algorithm, which created the classification rules as a decision tree (DT) structure from the first study area. …”
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A De-noising Scheme for Enhancing Power Quality Problem Classification System Based on Wavelet Transform and Rule-Based Method by Keow, Chuah Heng, Nallagownden, Perumal, K. S. , Rama Rao

“…A Power quality Classification system can easily extract features from the second detail signal obtained after Discrete Wavelet Transform and using these features to construct a Rule Based Algorithm for identifying types of disturbances that exist in the captured power signal. …”
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Breast cancer detection by using associative classifier with rule refinement method based on relevance feedback by Abubacker, Nirase Fathima, Azman, Azreen, Doraisamy, Shyamala, Azmi Murad, Masrah Azrifah

“…Several researchers have proposed the use of associative classifier that generates strong associations between features and reveals hidden relationship that can be missed by other classification algorithms. …”
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Power quality problem classification based on Wavelet Transform and a Rule-Based method by Nallagownden, Perumal

“…These features and together with the duration of disturbance of occurrence obtained from 1st level of detail, they form the criteria for a Rule-Based software algorithm for detecting different kinds of power quality disturbances effectively. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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A rule-based parameter aided with object-based classification approach for extraction of building and roads from WorldView-2 images by Ziaei, Zahra, Pradhan, Biswajeet, Mansor, Shattri

“…The three applied algorithms are support vector machines (SVMs), nearest neighbour (NN) and proposed rule-based system. …”
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

“…This reserarch adapted a methodology of computer vision and algorithms that exploit image segmentation, feature extraction and fuzzy classification to guide the research activities. …”
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Extraction and Optimization of Fuzzy Protein Sequences Classification Rules Using GRBF Neural Networks by Wang, Dianhui, Lee, Nung Kion, Dillon, Tharam S.

“…Traditionally, two protein sequences are classified into the same class if their feature patterns have high homology. These feature patterns were originally extracted by sequence alignment algorithms, which measure similarity between an unseen protein sequence and identified protein sequences. …”
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Holy Qur'an speech recognition system Imaalah checking rule for warsh recitation by Yousfi, Bilal, Zeki, Akram M.

“…Subsequently, after features extraction, a classification algorithm (Hidden Markov Models (HMM)) is employed to compare the features extracted in real-time with that available in the knowledge base.…”
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