Fuzzy accuracy
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This paper aims to propose a design of a type-2 fuzzy cerebellar model articulation controller for uncertain nonlinear systems, which achieves high stability and accuracy for controlling magnetic levitation systems.
10p viwalton 02-07-2024 0 0 Download
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In line with that research trend, this paper proposes a hybrid algorithm combining particle swarm optimization with the simulated annealing technique (PSO-SA) to optimize the length of intervals to improve forecasting accuracies.
19p vimurdoch 18-09-2023 7 4 Download
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In this paper, we build an incremental algorithm to find the approximate reduct according to the combined filter-wrapper approach. Experimental results on a number of sample datasets show that the proposed incremental algorithm is more efficient than some other incremental algorithms following the filter approach in terms of the number of reductive set attributes and classification accuracy.
8p vineville 08-02-2023 6 2 Download
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The experimental results showed that the proposed method functioned efficiently by showcasing the highest accuracy rate as compared to the one without imputations, with imputation by Fuzzy C-Means (FCM), and imputation by Fuzzy C-Means with Majority Vote (FCMMV).
24p spiritedaway36 28-11-2021 7 1 Download
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Objectives: The main objective of the dissertation is to research and develop fuzzy clustering techniques on remote sensing image data in order to improve accuracy and improve clustering quality of clustering algorithms.
162p armyofthedead 23-06-2021 22 3 Download
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The objective of the thesis: Proposes filter-wrapper algorithms for fuzzy rough set based attribute reduction in decision tables to reduce the cardinality of reduct and increase significantly the classification accuracy.
28p extraenglish 24-05-2021 12 3 Download
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The first is the hybrid filterwrapper algorithm proposal for finding the reduction set of the decision table using advanced fuzzy distance measurements and other measurements basing on fuzzy rough set to minimize2 the number of attributes of reduction set. Reduce and improve the accuracy of the classification model.
26p capheviahe27 23-02-2021 25 3 Download
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The paper depicts complete study about the second method with some proposed algorithms. It focuses mainly on binary classification with kNN and SVM for imbalanced data. Experiments and comparisons among related methods will confirm pros and coin of each method with respect to performance accuracy and time consumption.
20p viguam2711 11-01-2021 10 2 Download
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Quantitative traits or continuous outcomes related to complex diseases can provide more information and therefore more accurate analysis for identifying gene-gene and gene- environment interactions associated with complex diseases.
13p viconnecticut2711 28-10-2020 12 0 Download
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In this work, mangoes of three different phases or conditions were classified. This work is based on image processing technique to classify the condition of the mango through sample MATLAB tool. Image acquisition is carried out by collecting the sample images of mangoes manually to train the algorithm and to perform further processes of classifying and measuring the accuracy of classifying.
14p cleopatrahuynh 01-06-2020 12 2 Download
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The result showed that the influence of work piece material hardness on surface finish is significant for cutting speed and feed in CNC end milling operation. It is also observed that the surface roughness prediction accuracy of Adaptive neuro fuzzy inference system using triangular membership function is better than Gaussian, bell shape membership function and regression analysis. Surface roughness prediction accuracy with material hardness as input parameter is 97.61%.
8p toritori 11-05-2020 15 1 Download
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During last years, lots of the fuzzy rule based classifier (FRBC) design methods have been proposed to improve the classification accuracy and the interpretability of the proposed classification models. In view of that trend, genetic design methods of linguistic terms along with their (triangular and trapezoidal) fuzzy sets based semantics for FRBCs, using hedge algebras as the mathematical formalism, have been proposed.
18p 12120609 23-03-2020 27 2 Download
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In this paper, we propose a fuzzy distance based attribute reduction method on the decision table with numerical attribute value domain. Experiments on data sets show that the proposed method is more efficient than the ones based on Shannon’s entropy on the executed time and the classification accuracy of reduct.
9p vitomato2711 11-03-2020 23 0 Download
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In this paper we propose two ways to improve the accuracy of ECG signal recognition by filtering out the effect of the respiration in the ECG signal and by using the information of breathing stage as features in ECG signal classification. These approaches can improve the reliability and accuracy of the arrhythmia classification. As the classifier we use the modified neuro-fuzzy TSK network. The proposed solution will be tested with data from the MIT-BIH and the MGH/MF databases.
12p abcxyz123_02 03-03-2020 13 1 Download
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Runoff simulation models were developed to predict runoff for basin of West Godavari district, Andhra Pradesh by utilizing adaptive neuro-fuzzy inference system (ANFIS).Combinations of variables like previous three day stage, previous two day stage, previous one day stage, previous three day run off, previous two day run off, previous one day runoff as input and present day runoff as output were explored.
8p quenchua2 15-12-2019 24 0 Download
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In this paper, a novel FTS forecasting model based on fuzzy C-means (FCM) clustering and particle swarm optimization (PSO) was developed to enhance the forecasting accuracy. Firstly, the FCM clustering is used to divide the historical data into intervals with different lengths. After generating interval, the historical data is fuzzified into fuzzy sets.
26p viconandoyle2711 29-08-2019 34 2 Download
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This paper proposed a scheme combining both conventional P&O algorithm and a Feedforward compensator (P&O_FFC) adjusted by using FLC mechanism for improving the accuracy, and reducing oscillation in comparision with P&O or FLC applied in seperately.
9p viengland2711 23-07-2019 14 2 Download
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Thesis with the aim of focusing on two main issues. The first is time series modeling by states in which each state is a deterministic probability distribution (normal distribution). Based on the experimental results to assess the suitability of the model. Second, combine Markov chains and fuzzy time series into new models to improve forecast accuracy. Expand the model with high-level Markov chains to be compatible with seasonal data.
27p xacxuoc4321 11-07-2019 32 1 Download
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The results obtained indicate that the two algorithms are as efficient as the fuzzy k-Means algorithm when clustering numerical values. Further, on an ANOVA test, k-AMH Numeric I obtained the highest accuracy score of 0.69 for the six datasets combined with p-value less than 0.01, indicating a 95% confidence level.
13p meriday 20-04-2019 14 0 Download
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This paper proposed the cancer identification methods and evaluated them based on the computation time, classification accuracy and ability to reveal biologically meaningful gene information. This paper highlights the cancer gene identification using the Modified Fuzzy C-Means algorithm that is used efficiently in this work and examined with better results.
7p hongnhan878 12-04-2019 22 0 Download