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Book ChapterDOI

Fuzzy Logic Model for Multi-Reservoir Operation

01 Jan 2006-Vol. 1, pp 117-126
TL;DR: A non-magnetic molded plastic bobbin has a bore by which the bobbin is slip-fitted upon the cylindrical outer surface of the inner body carried by the rotating shaft.
Abstract: A non-magnetic molded plastic bobbin has a bore by which the bobbin is slip-fitted upon the cylindrical outer surface of the inner body carried by the rotating shaft. An integrally molded radial thrust flange at one end of the bobbin slip-fits against a radial flange of the inner body and defines an annular recess for the winding of a coil on the bobbin. The molded plastic bobbin also has an annular recess which extends concentric with the bore to receive the magnet body therewithin. A ridge is molded integrally with the bobbin on the wall thereof defining the magnet body annular recess and engages against the magnet body to retain the magnet body within the recess. A plurality of snap fingers are molded integrally with the bobbin and project inwardly from the bore thereof into slip-fitting relationship within an annular groove in the inner body to enable rotation of the inner body relative the stationary bobbin while retaining the bobbin axially relative the inner body. An integral axial extension of the bobbin abuts with a stationary clutch housing to retain the stationary field rotationally stationary during rotation of the inner body.
Citations
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Journal ArticleDOI
TL;DR: A model of Multi Objective Fuzzy Linear Programming (MOFLP) based on FuzzY Parametric Programming (FPP) to solve the problem of optimal cropping pattern in an irrigation system and takes into consideration the fuzziness involved in the coefficient of objective functions, technological coefficients and stipulations.
Abstract: The present paper proposes a model of Multi Objective Fuzzy Linear Programming (MOFLP) based on Fuzzy Parametric Programming (FPP) to solve the problem of optimal cropping pattern in an irrigation system. It has been found that in order to solve the problem of uncertainty in the planning of sustainable irrigation, the concept of fuzzy logic has been in practice for long and was being systematically applied either to the case of fuzzy objectives alone or to case of fuzzy objectives with fuzzy resources. There has not been reported a single case of either formulation and application of MOFLP model for the planning of irrigation making use of fuzzy objective function coefficients, fuzzy technological coefficients and fuzzy resources. The approach presented in the MOFLP model attempts to consider the fuzziness of all the coefficients of a mathematical model, as they present themselves in the real life situations. The present model takes into account the experience, information and expectations of the Decision Maker (DM). The objective of the model is to maximize simultaneously four objective functions viz. the Net Benefits (NB), Crop Production (CP), Employment Generation (EG) and Manure Utilization (MU). The model proposed takes into consideration the fuzziness involved in the coefficient of objective functions, technological coefficients and stipulations. The model intends to develop a program of sustainable irrigation planning for the Jayakwadi Project, Stage-I, located in the State of Maharashtra, India. The optimal cropping pattern has been obtained for five different strategies. The results finally obtained through the fifth strategy appear realistic, promising and effective as they involve the consideration of the uncertainty contained in coefficient of objective functions, technological coefficients and stipulations simultaneously. The model may be applied to any irrigation project with a view to utilize the resources available optimally and deal with the problem of uncertainty in realistic ways in solving real life problems.

16 citations


Cites background or methods from "Fuzzy Logic Model for Multi-Reservo..."

  • ...Raju and Duckstein (2003) attempted to develop the MOFLP model for planning sustainable irrigation considering fuzzy objectives and have pointed out many advantages of the FLP compared with other methods of multi-objective optimization such as Constraint and Weighting methods. For planning irrigation, Raju and Nagesh Kumar (2005) have come out with Fuzzy Decision System that is based on two fuzzy logic based MCDM Methods viz....

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  • ...…operating policies to the optimal operation of single reservoir as well as to the operation of multi reservoirs (Shrestha et al. 1996; Fontane et al. 1997; Panigrahi and Mujumdar 2000; Dubrovin et al. 2002; Timant et al. 2002; Mousavi et al. 2004; Mohan and Prasad 2006; Abolpour and Javan 2007)....

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  • ...Raju and Duckstein (2003) attempted to develop the MOFLP model for planning sustainable irrigation considering fuzzy objectives and have pointed out many advantages of the FLP compared with other methods of multi-objective optimization such as Constraint and Weighting methods. For planning irrigation, Raju and Nagesh Kumar (2005) have come out with Fuzzy Decision System that is based on two fuzzy logic based MCDM Methods viz. Similarity Analysis (SA) and Decision Analysis (DA). Tsakiris and Spiliotis (2006) came out with a Goal Programming (GP) approach using the fuzzy set theory to find out the cropping pattern for Thessaly Plain in Greece....

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  • ...There have been researches and studies wherein the fuzzy programming has been successfully applied in the development of reservoir operating policies to the optimal operation of single reservoir as well as to the operation of multi reservoirs (Shrestha et al. 1996; Fontane et al. 1997; Panigrahi and Mujumdar 2000; Dubrovin et al. 2002; Timant et al. 2002; Mousavi et al. 2004; Mohan and Prasad 2006; Abolpour and Javan 2007)....

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  • ...Raju and Duckstein (2003) attempted to develop the MOFLP model for planning sustainable irrigation considering fuzzy objectives and have pointed out many advantages of the FLP compared with other methods of multi-objective optimization such as Constraint and Weighting methods....

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Journal ArticleDOI
TL;DR: In this paper, an adaptive neuro-fuzzy inference system, Thomas-Fiering model and hidden Markov model were integrated in a simulation model for simulation of reservoir operation.
Abstract: This paper presents an integration of data-driven modeling and stochastic models for simulation of reservoir operation. The simulation model developed in this study was applied to the Ruhr river reservoirs system in Germany. An adaptive neuro-fuzzy inference system, Thomas–Fiering model and hidden Markov model were integrated in a simulation model. The set of model input included the time of the year, reservoir storage, inflow and Standardized Precipitation Index; and the target output was the reservoir release. Predicted and observed release values were evaluated using several common evaluation criteria. Results of model performance showed that the proposed model is capable of simulating reservoir operation and provides reliable reservoir release prediction. Results showed also that the proposed approach could be a good tool at the real-time operation stage to quickly check operational alternatives due to emergency events or planning and real-time incongruence.

9 citations

Book ChapterDOI
Mosaad Khadr1
01 Jan 2017
TL;DR: In this article, an adaptive neuro-fuzzy inference system (ANFIS) was used to predict water quality parameters in Manzala Lake based on water quality parameter of drains associated with the Lake.
Abstract: Egyptian coastal lakes, four lakes, and two lagoons represent about 25% of the Mediterranean total wetlands, and the four lakes are located at the north of Nile Delta and are known as Northern Delta Lakes. Manzala Lake, the largest of the Egyptian lakes, is affected qualitatively and quantitatively by drainage water that flows into the lake. In water quality modeling, deterministic models are frequently used to describe the system behavior. However most ecological systems are so complex and unstable. In some cases, the deterministic models have high chance of failure due to absence of prior information. A deterministic model may also have inevitably errors originated from model structures or other causes. For such cases, new modeling paradigm such as data-driven modeling or data mining has recently been a considerable growth in the development and application of computational intelligence and computer tools with respect to water-related problems. This chapter illustrates the capabilities of adaptive neuro-fuzzy inference system (ANFIS) to predict water quality parameters in Manzala Lake based on water quality parameters of drains associated with the Lake. A combination of data sets was considered as input data for ANFIS models, including discharge, pH, total suspended solids, electrical conductivity, total dissolved solids, water temperature, dissolved oxygen, salinity, and turbidity. The models were calibrated and validated against the measured data. The performance of the models was measured using various prediction skills criteria. Results show that ANFIS models are capable of simulating the water quality parameters and provided reliable prediction of total phosphorus and total nitrogen and, thus, suggesting the suitability of the proposed model as a tool for on-site water quality evaluation.

2 citations

References
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Journal ArticleDOI
TL;DR: A fuzzy rule-based control model for multipurpose real-time reservoir operation is constructed and a new, mathematically justified methodology for fuzzy inference—total fuzzy similarity—is used and compared with the more traditional Sugeno-style method.
Abstract: A fuzzy rule-based control model for multipurpose real-time reservoir operation is constructed. A new, mathematically justified methodology for fuzzy inference—total fuzzy similarity—is used and compared with the more traditional Sugeno-style method. Specifically, the seasonal variation in both hydrological variables and operational targets is examined by considering the inputs as season-dependent relative values, instead of using absolute values. The inference drawn in several stages allows a simple, accessible model structure. The control model is illustrated using Lake Paijanne, a regulated lake in Finland. The model is calibrated to simulate the actual operation, but also to better fulfill the new multipurpose operational objectives determined by experts. Relatively similar results obtained with the inference methods and the strong mathematical background of total fuzzy similarity put fuzzy reasoning on a solid foundation.

97 citations