Leveraging Artificial Intelligent Model for Water Quality Indices Assessment: A Comprehensive Study and Framework DOI

Hera Naeem,

Amir Ali Mokharzadeh,

Sara Khan

et al.

Published: Oct. 21, 2023

Potable water accessibility is becoming the scarcest matter all over world. It essential to assess quality indices. This paper, aimed create a user-friendly MATLAB interface tailored for practitioners with limited programming experience. built on base of natural phenomena and consists algorithmic complex solutions by combining particle swarm optimization (PSO) support vector machines (SVMs). employed fundamental Artificial Intelligent Machine Learning methods predict quality, merging PSO SVMs. investigation delved into classification predictive AI systems, leading development four individual models, hybrid metaheuristic regression model, ensemble techniques (stacking, voting, bagging). Initial focus singular technique, SVM. The primary goal propose versatile framework modeling. approach enhance both accuracy practical application models. resulting empowers administrators hydrologists select suitable analytical tools management using techniques. system shows 96% accurate result.

Language: Английский

Research on Coupling Coordination of Urban Infrastructure Resilience Based on Pressure-State-Response Model: A Case of Four Municipalities in China DOI
Min Chen, Qian Zhang, Yu Jiang

et al.

Published: Jan. 1, 2024

Download This Paper Open PDF in Browser Add to My Library Share: Permalink Using these links will ensure access this page indefinitely Copy URL DOI

Language: Английский

Citations

0

Using Borda and Bargaining algorithms to prioritize potential contamination of springs DOI Creative Commons

Ali Haghizadeh,

Mahsa Hassanvand,

Bahram kamarhei

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 19, 2024

Abstract The selection of an optimal decision-making method for water resource management is important and necessary. In this context, game theory makes a significant contribution to the advancement achieving outcomes due its high efficiency in solving multi-objective problems offering diverse modeling techniques. study, prioritization potential contamination springs Khorramabad was considered, by using Borda bargaining algorithms theory, most effective parameters critical resources terms were identified. Various parameters, including pH, NO3 etc., collected calculated studied entered into based on their importance creating pollution potential. Landsat 8 satellite's OLI sensor with imagery date 2017 utilized generate LU/LC map region. By employing scoring method, CO3, K, HCO3 effective, scores 232, 157.5 153.5, respectively. Implementing algorithm, pH 254, 177 165, Finally, presented both methods. Golestan Qeyu, ranked first. implementing Qeyu Dareh-Saki are as top priorities. Which these methods more suitable groundwater management, according guiding principles, depends preferences decision-makers goals management.

Language: Английский

Citations

0

Fractals and Finite Distributions of Power Sets DOI Open Access

Haosen Zheng,

Xiaopei Li

Journal of Physics Conference Series, Journal Year: 2023, Volume and Issue: 2449(1), P. 012008 - 012008

Published: March 1, 2023

Abstract In this paper, we are committed to investigating the fractal decomposition of power sets. Our main result is that every set can be decomposed into a sum and an isomorphic does not intersect with it. For finite set, property drawn on ordinal line by constructing number axis line, distribution graph obtained using parallel translation drawing method. Moreover, distributions do overlap or cross. The results in paper provide new perspective for further investigation

Language: Английский

Citations

0

Leveraging Artificial Intelligent Model for Water Quality Indices Assessment: A Comprehensive Study and Framework DOI

Hera Naeem,

Amir Ali Mokharzadeh,

Sara Khan

et al.

Published: Oct. 21, 2023

Potable water accessibility is becoming the scarcest matter all over world. It essential to assess quality indices. This paper, aimed create a user-friendly MATLAB interface tailored for practitioners with limited programming experience. built on base of natural phenomena and consists algorithmic complex solutions by combining particle swarm optimization (PSO) support vector machines (SVMs). employed fundamental Artificial Intelligent Machine Learning methods predict quality, merging PSO SVMs. investigation delved into classification predictive AI systems, leading development four individual models, hybrid metaheuristic regression model, ensemble techniques (stacking, voting, bagging). Initial focus singular technique, SVM. The primary goal propose versatile framework modeling. approach enhance both accuracy practical application models. resulting empowers administrators hydrologists select suitable analytical tools management using techniques. system shows 96% accurate result.

Language: Английский

Citations

0