Search Results - (( data optimization based algorithm ) OR ( rule extraction method algorithm ))

A new ant based rule extraction algorithm for web classification by Ku-Mahamud, Ku Ruhana, Saian, Rizauddin

“…Using Classifier-based attribute subset selection will reduce more attributes, but sacrifice the performance of the classifier.A hybrid ant colony optimization with simulated annealing algorithm to discover rules from data is proposed.The simulated annealing technique will minimize the problem of low quality discovered rule by an ant in a colony.The best rule for a colony will then be chosen and later the best rule among the colonies will be included in the rule set.The best rule for a colony will then be chosen and later the best rule among the colonies will be included in the rule set.The rule set is arranged in decreasing order of generation.Thirteen data sets which consist of discrete and continuous data were used to evaluate the performance of the proposed algorithm in terms of accuracy, number of rules and number of terms in the rules.Experimental results obtained from the proposed algorithm are comparable to the results of the Ant-Miner algorithm in terms of rule accuracy but are better in terms of rule simplicity.…”
Get full text
Get full text
Get full text
Get full text

Using genetic algorithms as image watermarking performance optimizer / Zuhaili Zahid by Zahid, Zuhaili

“…As a result, these errors will produce less accurate results during the process of extraction to the original watermark. Thus, this project will introduce a genetic-algorithms-based technique to overcome the rounding error problem. …”
Get full text
Get full text

Binary Artificial Bee Colony Optimization For Weighted Random 2 Satisfiability In Discrete Hopfield Neural Network by Muhammad Sidik, Siti Syatirah

“…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. …”
Get full text
Get full text

Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…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). …”
Get full text
Get full text
Get full text

GA optimization-based BRB AI reasoning algorithm for determining the factors affecting customer churn for operators by Kun, Liu, Alli, Hassan, Abd Rahman, Khairul Aidil Azlin

“…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. …”
Get full text
Get full text
Get full text

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. 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). …”

Integration of knowledge-based seismic inversion and sedimentological investigations for heterogeneous reservoir by Shahbazi, A., Monfared, M.S., Thiruchelvam, V., Ka Fei, T., Babasafari, A.A.

“…The extracted rules and optimized number rules then would be used for rule-based porosity estimation. …”
Get full text
Get full text

Enhancing project completion date prediction using a hybrid model: rule-based algorithm and machine learning algorithm by Abd Rahman, Mohd Shahrizan, Jamaludin, Nor Azliana Akmal, Zainol, Zuraini, Tengku Sembok, Tengku Mohd

“…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. …”
Get full text
Get full text
Get full text

Logic Mining Approach: Shoppers’ Purchasing Data Extraction via Evolutionary Algorithm by Mohd Kasihmuddin, Mohd Shareduwan, Abdul Halim, Nur Shahira, Mohd Jamaludin, Siti Zulaikha, Mansor, Mohd. Asyraf, Alway, Alyaa, Zamri, Nur Ezlin, Azhar, Siti Aishah, Marsani, Muhammad Fadhil

“…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. …”
Get full text
Get full text
Get full text
Get full text

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

“…From news classification and news sentiment, a rule-based algorithm was used to predict the stock market turning points. …”
Get full text
Get full text

Context enrichment framework for sentiment analysis in handling word ambiguity resolution by Yusof, Nor Nadiah

“…The model incorporates a proposed negation rule-based method that considers the threshold value condition of negative words in the documents. …”
Get full text
Get full text

Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

“…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
Get full text
Get full text

A study on component-based technology for development of complex bioinformatics software by Ali Shah, Zuraini, Deris, Safaai, Othman, Muhamad Razib, Zakaria, Zalmiyah, Saad, Puteh, Hassan, Rohayanti, Muda, Mohd. Hilmi, Kasim, Shahreen, Roslan, Rosfuzah

“…The second layer uses discriminative SVM algorithm with a state-of-the-art string kernel based on PSI-BLAST profiles that is used to leverage the unlabeled data. …”
Get full text
Get full text

Ensemble model of non-linear feature selection-based Extreme Learning Machine for improved natural gas reservoir characterization by Fatai Adesina, Anifowose, Jane, Labadin, Abdulazeez, Abdulraheem

“…The deluge of multi-dimensional data acquired from advanced data acquisition tools requires sophisticated algorithms to extract useful knowledge from such data. …”
Get full text
Get full text
Get full text

Topic identification using filtering and rule generation algorithm for textual document by Nurul Syafidah, Jamil

“…The rule generation algorithm (TopId) is proposed to identify topic for each verse based on the extracted terms. …”
Get full text
Get full text
Get full text

Compressing and improving fuzzy rules using genetic algorithm and its application to fault detection by Yap K.S., Wong S.Y., Tiong S.K.

“…The improved model is applied to two benchmark problems, and the rules extracted are analyzed, discussed and compared with other published methods. …”

The framework of weighted subset-hood Mamdani fuzzy rule based system rule extraction (MFRBS-WSBA) for forecasting electricity load demand by Mansor, Rosnalini, Mat Kasim, Maznah, Othman, Mahmod

“…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…”
Get full text
Get full text

The framework of weighted subset-hood Mamdani fuzzy rule based system rule extraction (MFRBS-WSBA) for forecasting electricity load demand by Mansor, R., Kasim, M.M., Othman, M.

“…These preliminary results show that the WSBA method can be one of alternative methods to extract fuzzy rules for forecast electricity load demand. …”
Get full text
Get full text

Hybrid subjective evaluation method using weighted subsethood - based (WSBA) rule generation algorithm by Othman, Mahmod, Khalid, Shaiful Annuar, Abdullah, Fader, Amir Hamzah, Shezrin Hawani, Ku-Mahamud, Ku Ruhana

“…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.…”
Get full text
Get full text
Get full text

Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

“…The extraction of minimum rules operation is conducted after the default rules have been generated in order to obtain the most useful discovered rules. …”
Get full text
Get full text