An Algorithm for Optimal Allocation of Water Resources in Receiving Areas Based on Adaptive Decreasing Inertia Weights
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Post-publication record
- Nature
- Retraction
- Reason
- Concerns/Issues about Data;Concerns/Issues about Results and/or Conclusions;Concerns/Issues about Referencing/Attributions;Concerns/Issues about Peer Review;Investigation by Journal/Publisher;Investigation by Third Party;Paper Mill;Computer-Aided Content or Computer-Generated Content;Unreliable Results and/or Conclusions;
- Date
- 8/9/2023 0:00
- Flagged by OpenAlex?
- Yes
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Abstract
As the biggest rigid constraint for high-quality economic and social development, how to improve the carrying capacity of water resources, realize the stable and coordinated development of water resources-ecological environment-economic and social integrated system, and provide water resources guarantee for regional transformation and upgrading development is a major issue in the current social development. This paper firstly selects the minimum loss of water resources allocation as the objective function for mathematical modelling, chooses the particle swarm algorithm as the objective algorithm, and proposes a particle swarm algorithm based on the standard particle swarm algorithm with improved adaptive decreasing inertia weights. It is a time-varying process for the inertia weights and acceleration factors of the standard particle swarm algorithm so that they change nonlinearly with the continuous advancement of the iterative optimization seeking process, thus improving the convergence accuracy and speed of the algorithm and reducing the risk of falling into local optimum solutions at a later stage. Finally, based on the actual installation of the current water distribution reactive power compensation device, the shunt distributor set is selected as the reactive power compensation device, sensitivity analysis is applied to the load nodes for sensitivity calculation, and the nodes requiring compensation are connected to the shunt distributor set for flexible and optimal configuration. The stronger local search capability of the inertia weight adaptive decreasing algorithm is utilized in the generation process of new particles to perform a local search operation for particles, which avoids premature convergence and improves the search performance of the algorithm. To realize the rational allocation of water resources, a multiobjective receiving area water resources optimization allocation model with maximum water supply benefit, minimum regional water shortage, and minimum pollutant emission is established.
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The record
- Venue
- Journal of Advanced Transportation
- Topic
- Water resources management and optimization
- Field
- Engineering
- Canadian institutions
- —
- Funders
- Wuhan University of TechnologyWuhan University
- Keywords
- Particle swarm optimizationInertiaMathematical optimizationComputer scienceSwarm behaviourAlgorithmSensitivity (control systems)DistributorConvergence (economics)Process (computing)Local optimumControl theory (sociology)EngineeringMathematicsArtificial intelligence
- Has abstract in OpenAlex
- yes