Least squares model fitting to fuzzy vector data
Fuzzy Sets and Systems
Information Sciences: an International Journal
Evaluation of fuzzy linear regression models
Fuzzy Sets and Systems
Fuzzy Sets and Systems
Exponential possibility regression analysis
Fuzzy Sets and Systems - Special issue on fuzzy information processing
Fuzzy regression methods—a comparative assessment
Fuzzy Sets and Systems
Industrial Applications of Fuzzy Control
Industrial Applications of Fuzzy Control
Interval regression analysis by quadratic programming approach
IEEE Transactions on Fuzzy Systems
An adaptive neuro-fuzzy inference system for bridge risk assessment
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
A fuzzy logic based efficient energy saving approach for domestic heating systems
Integrated Computer-Aided Engineering
Energy saving by means of fuzzy systems
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
An evolving-onstruction scheme for fuzzy systems
IEEE Transactions on Fuzzy Systems
Complex-fuzzy adaptive image restoration: an artificial-bee-colony-based learning approach
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part II
Complex fuzzy computing to time series prediction: a multi-swarm PSO learning approach
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part II
Adaptive image restoration by a novel neuro-fuzzy approach using complex fuzzy sets
International Journal of Intelligent Information and Database Systems
Hi-index | 0.21 |
The methods of ordinary least-squares regression (OLSR), fuzzy regression (FR), and adaptive network-based fuzzy inference system (ANFIS) are compared in inferring operating rules for a reservoir operations optimization problem. Dynamic programming (DP) is used as an example optimization tool to provide the input-output data set to be used by OLSR, FR, and ANFIS models. The coefficients of an FR model are found by solving a linear programming (LP) problem. The objective function of the LP is to minimize the total fuzziness of the FR model, which is related to the width of fuzzy coefficients in the regression model. Before applying FR to the reservoir operations problem, two FR formulations and interval regression (IR) are first examined in a simple tutorial example. ANFIS is also used to derive the reservoir operating rules as fuzzy IF-THEN rules. The OLSR, FR, and ANFIS based rules are then simulated and compared based on their performance in simulation. The methods are applied to a long-term planning problem as well as to a medium-term implicit stochastic optimization model. The results indicate that FR is useful to derive operating rules for a long-term planning model, where imperfect and partial information is available. ANFIS is beneficial in medium-term implicit stochastic optimization as it is able to extract important features of the system from the generated input-output set and represent those features as general operating rules.