A bio-inspired algorithm for a classical water resources allocation problem based on Adleman-Lipton model

Deng, Anjun; Wang, Zhaocai; Liu, Haifeng; Wu, Tunhua

doi:10.5004/dwt.2020.25453

Cited by 9 publications

(2 citation statements)

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“…The Grey model is a prediction model based on the grey theory, which is mainly applied in the uncertain background of fewer data and information. Through data processing and analysis, it can achieve the establishment of a prediction model, predict the development trend, and make a reasonable evaluation (Ding 2018;Deng et al 2020e). Wang et al (2021b) used the optimized Grey-Markov model to forecast the domestic water consumption in the Shaanxi Province of China.…”

Section: Current Status Of Research On Water Resources Predictionmentioning

confidence: 99%

Prediction and analysis of water resources demand in Taiyuan City based on principal component analysis and BP neural network

Wang

Dong

2021

Journal of Water Supply: Research and Technology-Aqua

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Water is a fundamental natural and strategic economic resource that plays a vital role in promoting economic and social development. With the accelerated urbanization and industrialization in China, the potential demand for water resources will be enormous. Therefore, accurate prediction of water resources demand is important for the formulation of industrial and agricultural policies, development of economic plans, and many other aspects. In this study, we develop a model based on principal component analysis (PCA) and back propagation (BP) neural network to predict water resources demand in Taiyuan, Shanxi Province, a city with severe water shortage in China. The prediction accuracy is then compared with PCA-ANN, ARIMA, NARX, Grey–Markov, serial regression, and LSTM models, and the results showed that the PCA-BP model outperformed other models in many evaluation factors. The proposed PCA-BP model reduces the dimensionality of high-dimensional variables by PCA and transformed them into uncorrelated composite data, which can make them easier to compute. More importantly, BP and weight threshold adjustment in model training further improve the prediction accuracy of the model. The model analysis will provide an important reference for water demand assessment and optimal water allocation in other regions.

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Section: Current Status Of Research On Water Resources Predictionmentioning

confidence: 99%

Prediction and analysis of water resources demand in Taiyuan City based on principal component analysis and BP neural network

Wang

Dong

2021

Journal of Water Supply: Research and Technology-Aqua

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“…In addition, they applied the FLOW3D software to complete the numerical simulations of the stepped spillway. Denga et al (2020) used the Adleman-Lipton model as a bio-inspired algorithm in their study. Wang et al (2021) used the optimized grey and Markov models for predicting domestic water consumption.…”

Section: Introductionmentioning

confidence: 99%

Genetic algorithms for optimizing stepped spillways to maximize energy dissipation

Salmasi

Abraham

2021

Water Supply

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Stepped spillways are important water-management structures that are used for energy dissipation. Use of these spillways has increased in recent decades, they can reduce construction time and they are effective for reducing the flow's downstream kinetic energy. In this study, the width and height of the steps as well as the slope and height of the overflow spillway were considered as variables. Due to the large number of variables, non-linearity of the objective function and constraints, and the lack of an explicit relationship between decision variables, a genetic algorithm (GA) was used. A stepped spillway with optimal dimensions was proposed as a replacement of the smooth spillway of Sarogh Dam located in West Azerbaijan province, Iran. The proposed steps increase energy dissipation; for constant discharge and varying slopes, the changes in the optimal height of the steps were insignificant. Sensitivity analysis using the objective function showed that the relative energy dissipation for a constant discharge is independent of the optimal height of the steps and decreases with increasing spillway slope. In addition, for fixed slopes, increasing the flow rate leads to a decrease in relative energy dissipation and an increase in the optimal height of the steps.

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Sustainable Spectrum Allocation Strategy for 5G Mobile Network

Deb

2022

Wireless Pers Commun

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A bio-inspired algorithm for a classical water resources allocation problem based on Adleman-Lipton model

Cited by 9 publications

References 0 publications

Prediction and analysis of water resources demand in Taiyuan City based on principal component analysis and BP neural network

Prediction and analysis of water resources demand in Taiyuan City based on principal component analysis and BP neural network

Genetic algorithms for optimizing stepped spillways to maximize energy dissipation

Sustainable Spectrum Allocation Strategy for 5G Mobile Network

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