Search Results - (( rule extraction method algorithm ) OR ( based optimization model algorithm ))
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Compressing and improving fuzzy rules using genetic algorithm and its application to fault detection
Published 2023“…The O-EGART-PR-FIS approach can achieve the highest accuracy rate among all, however the extracted rules are less compact. Hence, in this paper, we propose a genetic algorithm based method with the inclusion of the 'Don't Care' antecedent (hereafter denoted as DC-GA) to the foundation of the O-EGART-PR-FIS, with the aim of further optimizing the existing fuzzy rules. …”
Conference Paper -
2
Improved Malware detection model with Apriori Association rule and particle swarm optimization
Published 2019“…These rule models are used together with extraction algorithm to classify and detect malicious android application. …”
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3
Binary Artificial Bee Colony Optimization For Weighted Random 2 Satisfiability In Discrete Hopfield Neural Network
Published 2023“…This proposed model will be employed in the Improved Reverse Analysis method to extract the relationship between various fields of real-life data sets based on logical representation. …”
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4
Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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5
GA optimization-based BRB AI reasoning algorithm for determining the factors affecting customer churn for operators
Published 2024“…Therefore, in this paper, a belief rule base (BRB) artificial intelligence inference algorithm based on GA optimization to determine the factors affecting customer churn for operators proposed. …”
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Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun
Published 2021“…Apart from that, having low values in four of the performance criteria: RMSE, MAE, NSE, and RSR, have further strengthened the credibility of the results. As for the optimization process, the reservoir operation rule was derived using a meta-heuristic algorithm at the monthly interval. …”
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7
Integration of knowledge-based seismic inversion and sedimentological investigations for heterogeneous reservoir
Published 2020“…The extracted rules and optimized number rules then would be used for rule-based porosity estimation. …”
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A genetic algorithm based fuzzy inference system for pattern classification and rule extraction
Published 2023“…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. This paper presents a genetic-algorithm-based fuzzy inference system for extracting highly comprehensible fuzzy rules to be implemented in human practices without detailed computation (hereafter denoted as GA-FIS). …”
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Enhancing project completion date prediction using a hybrid model: rule-based algorithm and machine learning algorithm
Published 2025“…The study employs a hybrid predictive model that combines Big Data technologies, Extract Load Transfer (ELT) processes, rule-based algorithms (RBA), machine learning (ML), and Power BI visualizations. …”
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Logic Mining Approach: Shoppers’ Purchasing Data Extraction via Evolutionary Algorithm
Published 2023“…In reducing the learning complexity, a genetic algorithm was implemented to optimize the logical rule throughout the learning phase in performing a 2-satisfiability-based reverse analysis method, implemented during the learning phase as this method was compared. …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.]
Published 2021“…From news classification and news sentiment, a rule-based algorithm was used to predict the stock market turning points. …”
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Book Section -
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Context enrichment framework for sentiment analysis in handling word ambiguity resolution
Published 2024“…A NAM is implemented within the negation scope to accurately address negation. The model incorporates a proposed negation rule-based method that considers the threshold value condition of negative words in the documents. …”
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13
Real-time oil palm fruit bunch ripeness grading system using image processing techniques
Published 2013“…These results are optimal based on the thorns model. A new approach was developed using expert rules-based system. …”
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14
Ensemble model of non-linear feature selection-based Extreme Learning Machine for improved natural gas reservoir characterization
Published 2015“…The deluge of multi-dimensional data acquired from advanced data acquisition tools requires sophisticated algorithms to extract useful knowledge from such data. …”
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Classification with degree of importance of attributes for stock market data mining
Published 2004“…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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Topic identification using filtering and rule generation algorithm for textual document
Published 2015“…The rule generation algorithm (TopId) is proposed to identify topic for each verse based on the extracted terms. …”
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A new ant based rule extraction algorithm for web classification
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Monograph -
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The framework of weighted subset-hood Mamdani fuzzy rule based system rule extraction (MFRBS-WSBA) for forecasting electricity load demand
Published 2016“…The objective of this paper is to show the fourth step in the framework which applied the new electricity load forecasting rule extraction by WSBA method. Electricity load demand in Malaysia data is used as numerical data in this framework.These preliminary results show that the WSBA method can be one of alternative methods to extract fuzzy rules for forecast electricity load demand…”
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The framework of weighted subset-hood Mamdani fuzzy rule based system rule extraction (MFRBS-WSBA) for forecasting electricity load demand
Published 2016“…These preliminary results show that the WSBA method can be one of alternative methods to extract fuzzy rules for forecast electricity load demand. …”
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20
Hybrid subjective evaluation method using weighted subsethood - based (WSBA) rule generation algorithm
Published 2013“…The use of fuzzy rules, which were extracted directly from input data through Weighted Subsethood-based (WSBA) Rule Generation Algorithm.WSBA rule generation use the subsethood values to generate the weights which finally produced the fuzzy general rules.The rules generated through the data provided knowledge in developed fuzzy rule The fuzzy rules embedded in the framework of subjective evaluation method showed advantages in generalizing the evaluation of the performance achievement, where the evaluation process can be conducted consistently in producing good evaluation results with the use of the membership set score.The results from the numerical examples are comparable to other fuzzy evaluation methods, even with the use of small rule size.…”
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