Evaluating weapon systems using fuzzy arithmetic operations
Fuzzy Sets and Systems
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
A TSK type fuzzy rule based system for stock price prediction
Expert Systems with Applications: An International Journal
Newspaper demand prediction and replacement model based on fuzzy clustering and rules
Information Sciences: an International Journal
Multi-attribute fuzzy time series method based on fuzzy clustering
Expert Systems with Applications: An International Journal
A fuzzy logic approach to forecast energy consumption change in a manufacturing system
Expert Systems with Applications: An International Journal
Takagi-Sugeno neural fuzzy modeling approach to fluid dispensing for electronic packaging
Expert Systems with Applications: An International Journal
Comparison of fuzzy reasoning methods
Fuzzy Sets and Systems
Temperature prediction using fuzzy time series
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Supervised fuzzy clustering for rule extraction
IEEE Transactions on Fuzzy Systems
Fuzzy rule interpolation for multidimensional input spaces with applications: a case study
IEEE Transactions on Fuzzy Systems
Interpolation with function space representation of membership functions
IEEE Transactions on Fuzzy Systems
Fuzzy Interpolation and Extrapolation: A Practical Approach
IEEE Transactions on Fuzzy Systems
Enhanced Fuzzy System Models With Improved Fuzzy Clustering Algorithm
IEEE Transactions on Fuzzy Systems
Fuzzy Interpolative Reasoning for Sparse Fuzzy-Rule-Based Systems Based on the Areas of Fuzzy Sets
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Multi-variable fuzzy forecasting based on fuzzy clustering and fuzzy rule interpolation techniques
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
An efficient time series forecasting model based on fuzzy time series
Engineering Applications of Artificial Intelligence
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In this paper, we present a new method to deal with temperature prediction based on fuzzy clustering and fuzzy rules interpolation techniques. First, the proposed method constructs fuzzy rules from training samples based on the fuzzy C-Means clustering algorithm, where each fuzzy rule corresponds to a cluster and the linguistic terms appearing in the fuzzy rules are represented by triangular fuzzy sets. Then, it performs fuzzy inference based on the multiple fuzzy rules interpolation scheme, where it calculates the weight of each fuzzy rule with respect to the input observation based on the defuzzified values of triangular fuzzy sets. Finally, it uses the weight of each fuzzy rule to calculate the forecasted output. We also apply the proposed method to handle the temperature prediction problem. The experimental result shows that the proposed method gets higher average forecasting accuracy rates than Chen and Hwang's method [7].