Search Results - (( based estimation method algorithm ) OR ( rule extraction method algorithm ))

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.

“…In this study, we present a knowledge based seismic acoustic impedance inversion method which employs rule based method for porosity estimation. …”
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Improving performance of automated coronary arterial tree center-line extraction, stent localization and tracking by Boroujeni, Farsad Zamani

“…The first contribution is automatic detection of seed points which serve as a prerequisite step for centerline extraction algorithm. The solution consists of an algorithm for automatic collection of candidate seed points using efficient grid line searching mechanism and a validation method which uses local geometric and intensity based features as effective validation rules to discriminate between the actual seed point and false alarms. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. 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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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

“…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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Semi-automatic oil palm tree counting from pleiades satellite imagery and airborne LiDAR / Nurul Syafiqah Khalid by Khalid, Nurul Syafiqah

“…The study is to categorize and evaluates methods for automatic tree counting detection. For the methodology of this study, object-based image analysis (OBIA), watershed transformation segmentation and local maxima algorithm are applied. …”
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Prediction of breast cancer relapse time in continuous scale based on type-2 TSK fuzzy model by Mahmoudian, Sayed Hamid

“…In addition, K-fold Cross Validation, B632 and B632+ methods have been used for error estimation. In the first objective of the thesis, a lemma has been proven and a new hybrid algorithm based on Fuzzy Association Rule Mining has been proposed to gather some selected genes and generate fuzzy rules for classification. …”
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Engine fault diagnosis using probabilistic neural network by Sheng, Zhu, Min, Keng Tan, Ka, Renee Yin Chin, Bih, Lii Chua, Xiaoxi, Hao, Tze, Kenneth Kin Teo

“…The proposed PNN is trained using the collected engine fault data from experiment and the probability density of PNN is determined based on the Parzen window estimation method. Bayes decision rule is implemented for classifying the types of the engine faults. …”
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Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition by Burhan, Nuradebah

“…Electromyography (EMG) signal is a biomedical signal which measures physical activity of human muscle.It has been acknowledged to be widely used in rehabilitation or recovery application system assisting physiotherapist to monitor a patient’s physical strength,function,motion and overall well-being by addressing the underlying physical issues.In application system associated with rehabilitation,a signal processing and classification techniques are implemented to classify EMG signal obtained.For real time application in the rehabilitation, the classification is crucial issue.The success of the signal classification depends on the selection of the features that represent a raw EMG signal in the signal processing.Therefore,a robust and resilient denoising method and spectral estimation technique have been acknowledged as necessary to distinguish and detect the EMG pattern.The present study was undertaken to determine the characteristic of EMG features using denoising method and spectral estimation technique for assessing the EMG pattern based on a supervised classification algorithm.In the study,the combination of time-frequency domain (TFD) and time domain (TD) were identified as the preferred denoising method and spectral estimation techniques.In the first part of study, the recorded EMG signal filtered the contaminated noise by using wavelet transform (WT) approach which implemented discrete wavelet transform (DWT) method of the wavelet-denoising signal. …”
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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. …”
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A new ant based rule extraction algorithm for web classification by Ku-Mahamud, Ku Ruhana, Saian, Rizauddin

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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…”
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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. …”
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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.…”
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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. …”
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A weighted subsethood mamdani fuzzy rules based system rule extraction (MFRBS-WSBA) for forecasting electricity load demand – a framework by Mansor, Rosnalini, Mat Kasim, Maznah, Othman, Mahmod

“…Specifically, this paper proposed two frameworks: MFRBSWSBA and WSBA framework where the WSBA is embedded in MFRBS-WSBA (fourth step in MFRBS-WSBA).The objective of this paper is to show the fourth step in the MFRBS-WSBA framework which applied the new electricity load forecasting rule extraction by WSBA method.We apply the proposed WSBA framework in Malaysia electricity load demand data as a numerical example in this paper.These preliminary results show that the WSBA framework can be one of alternative methods to extract fuzzy rules for forecast electricity load demand where the proposed method provide a simple to interpret the fuzzy rules and also offer a new direction to interpret the fuzzy rules compared to classical fuzzy rules…”
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Overview of biomedical relations extraction using hybrid rule-based approaches. by Abdul Kadir, Rabiah, Bokharaeian, Behrouz

“…However, in this work we will discuss the overview a combination of three methods called as hybrid rule-based to extract complex and simple relations.…”
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Frequent Lexicographic Algorithm for Mining Association Rules by Mustapha, Norwati

“…The primary concept of association rule algorithms consist of two phase procedure. In the first phase, all frequent patterns are found and the second phase uses these frequent patterns in order to generate all strong rules. …”
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A weighted subsethood mamdani fuzzy rules based system rule extraction (MFRBS-WSBA) for forecasting electricity load demand - A framework by Mansor, R., Mat Kasim, M., Othman, M.

“…These preliminary results show that the WSBA framework can be one of alternative methods to extract fuzzy rules for forecast electricity load demand where the proposed method provide a simple to interpret the fuzzy rules and also offer a new direction to interpret the fuzzy rules compared to classical fuzzy rules.…”
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A weighted subsethood mamdani fuzzy rules based system rule extraction (MFRBS-WSBA) for forecasting electricity load demand - A framework by Mansor, R., Mat Kasim, M., Othman, M.

“…These preliminary results show that the WSBA framework can be one of alternative methods to extract fuzzy rules for forecast electricity load demand where the proposed method provide a simple to interpret the fuzzy rules and also offer a new direction to interpret the fuzzy rules compared to classical fuzzy rules.…”
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