Regulation of water resources systems using fuzzy logic: a case study of Amaravathi dam

Moorthi, P.V.P.; Singh, Ajit Pratap; Agnivesh, P.

doi:10.1007/s13201-018-0777-8

Cited by 18 publications

(15 citation statements)

References 17 publications

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“…To check the applicability of our optimization model, we first used the optimization model for non-pandemic scenarios, which includes the equations from Eq (12) to Eq (25), excluding Eq ( 14), (19), and (20). The results obtained from the model are presented in figure 3.…”

Section: Fraction Of Pucca House People Evacuatedmentioning

confidence: 99%

“…There is also a competition among the villages to have the highest possible evacuations, where the total number of evacuees is highly constrained due to the pandemic (Figure 1(a-b)). We address these multiple objectives using the max-min approach of multi-objective optimization, which has been widely used in areas such as water resources management (23)(24)(25), waste load allocations for water quality management in a stream (26)(27)(28)(29). The model is applied to a flood-prone district on the east coast of India, the Jagatsinghpur district in Odisha.…”

Section: Introductionmentioning

confidence: 99%

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Flood evacuation during pandemic: a multi-objective framework to handle compound hazard

Tripathy

Bhatia

Mohanty

et al. 2021

Environ. Res. Lett.

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The evacuation of the population from flood-affected regions is a non-structural measure to mitigate flood hazards. Shelters used for this purpose usually accommodate a large number of flood evacuees for a temporary period. Floods during a pandemic result in a compound hazard. Evacuations under such situations are difficult to plan as social distancing is nearly impossible in the highly crowded shelters. This results in a multi-objective problem with conflicting objectives of maximizing the number of evacuees from flood-prone regions and minimizing the number of infections at the end of the shelter’s stay. To the best of our knowledge, such a problem is yet to be explored in literature. Here we develop a simulation-optimization framework, where multiple objectives are handled with a max–min approach. The simulation model consists of an extended Susceptible—Exposed—Infectious—Recovered—Susceptible model. We apply the proposed model to the flood-prone Jagatsinghpur district in the state of Odisha, India. We find that the proposed approach can provide an estimate of people required to be evacuated from individual flood-prone villages to reduce flood hazards during the pandemic. At the same time, this does not result in an uncontrolled number of new infections. The proposed approach can generalize to different regions and can provide a framework to stakeholders to manage conflicting objectives in disaster management planning and to handle compound hazards.

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Section: Fraction Of Pucca House People Evacuatedmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Flood evacuation during pandemic: a multi-objective framework to handle compound hazard

Tripathy

Bhatia

Mohanty

et al. 2021

Environ. Res. Lett.

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“…However, some researchers discussed the limitations and complexity of these optimization models and the necessity of using more flexible and expert based knowledge approaches (such as Fuzzy Logic) in reservoir operation modelling [2,3]. In recent studies of ambiguity, modeling has focused on fuzzy logic-based approaches to regulate water resources systems [4,5]. Tilmant et al [6] made a comparison study between reservoir operating policies obtained from fuzzy and nonfuzzy explicit stochastic dynamic programming.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Logic Model for Optimal Operation of Darbandikhan Reservoir, Iraq

Faris¹,

Ibrahim²,

Abdulrahman³

et al. 2021

IJDNE

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The operating system of a reservoir is a significant contributor to its success in water resources management. For a multi-purpose reservoir, an ideal operating system determines output characteristics that take account of all objectives. In this study, a new model to optimize Darbandikhan reservoir system operation in Iraq is proposed, based on a fuzzy logic controller. The aim of the new system is to maximize hydropower production while satisfying all downstream water demands. The proposal was tested on flow and other data in 324 monthly time steps, from January 1992 to December 2018, using a simulation model based on the Simulink technique of MATLAB software. Trial and error showed that membership functions of the Gaussian shape were most appropriate. For comparison purposes, Discrete Differential Dynamic Programming (DDDP), Nonlinear Programming (NLP) and Linear Programming (LP) optimization models were developed and applied to operate the reservoir. The results for turbine operation show that, relative to actual power produced, average monthly hydropower generation is increased by 32.2% (fuzzy logic), 51.4% (DDDP), 29.3% (NLP), 27.4% (LP). Although the dynamic programming method generated more hydropower, the fuzzy logic controller avoided complex optimization procedures, making it more flexible and more acceptable to operators. Moreover, the fuzzy approach provides an opportunity for reservoir operators to develop and apply more convenient operating rules, which in itself is a valuable alternative to conventional optimization techniques.

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“…GIS-based fuzzy rule systems are proposed in the literature in which the Mamdani model [7,12,13], the Tagaki-Sugeno model [14,15] and a hybrid model [16] are applied. In this research we use the Mamdani fuzzy rule-based model proposed in [7], in which a center of gravity (CoG) method [17] is used in the defuzzification process.…”

Section: Introductionmentioning

confidence: 99%

A Fuzzy Rule-Based GIS Framework to Partition an Urban System Based on Characteristics of Urban Greenery in Relation to the Urban Context

Cardone

Martino

2020

Applied Sciences

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We present a Geographical Information System (GIS)-based framework implementing a Mamdani fuzzy rule-based system to partition in an unsupervised mode an urban system in urban green areas. The proposed framework is characterized by high usability and flexibility. The study area is partitioned into homogeneous regions regarding the characteristics of public green areas and relations with the residents and buildings. The urban system is initially partitioned into microzones, given the smallest areas in which a census of the urban system is taken in terms of resident population, type and number of buildings and properties, and industrial and service activities. During a pre-processing phase, the values of specific indicators defined by a domain expert, which characterize the type of urban green area and the relationship with the residents and buildings, are calculated for each microzone. Subsequently, the fuzzy rule-based system component is executed to classify each microzone based on the fuzzy rule set constructed by the domain expert. Spatially adjoining microzones belonging to the same class are dissolved to form homogeneous areas called urban green contexts. The membership degrees of the microzones to the fuzzy set of their class are used to evaluate the reliability of the classification of the urban green context. We test our framework on the municipality of Pozzuoli, Italy, comparing the results with the ones obtained in a supervised manner by the expert appropriately partitioning and classifying the urban study area based on his knowledge of it.

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Regulation of water resources systems using fuzzy logic: a case study of Amaravathi dam

Cited by 18 publications

References 17 publications

Flood evacuation during pandemic: a multi-objective framework to handle compound hazard

Flood evacuation during pandemic: a multi-objective framework to handle compound hazard

Fuzzy Logic Model for Optimal Operation of Darbandikhan Reservoir, Iraq

A Fuzzy Rule-Based GIS Framework to Partition an Urban System Based on Characteristics of Urban Greenery in Relation to the Urban Context

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