AIMC Topic: Models, Theoretical

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Fuzzy multi-objective optimization for sustainable agricultural water management of irrigation networks.

Journal of environmental management
Sustainable water resource management in arid and water deficit regions requires optimal use of water resources due to competition among different water sectors. The purpose of this study is to model uncertainties in economic and hydro-climatic varia...

Incorporating dynamic drainage supervision into deep learning for accurate real-time flood simulation in urban areas.

Water research
Urban flooding has become a prevalent issue in cities worldwide. Urban flood dynamics differ significantly from those in natural watersheds, primarily because of the intricate drainage systems and the high spatial heterogeneity of urban surfaces, whi...

Machine learning models for prediction of nutrient concentrations in surface water in an agricultural watershed.

Journal of environmental management
Prediction and quantification of nutrient concentrations in surface water has gained substantial attention during recent decades because excess nutrients released from agricultural and urban watersheds can significantly deteriorate surface water qual...

Bipolar Fuzzy Pseudo-UP Ideal Of Pseudo-UP Algebra.

F1000Research
In this paper, we apply the concept of bipolar fuzzy sets to pseudo-UP ideals in pseudo-UP algebras. We prove that the intersection of two bipolar fuzzy pseudo-UP ideals is also a bipolar fuzzy pseudo-UP ideal, while the union of two such ideals does...

Modelling and evaluation of mechanical performance and environmental impacts of sustainable concretes using a multi-objective optimization based innovative interpretable artificial intelligence method.

Journal of environmental management
This study focuses on modelling sustainable concretes' mechanical and environmental properties with interpretable artificial intelligence-based automated rule extraction, management of waste materials, and meeting future prospects. In this context, 2...

Efficient deep learning surrogate method for predicting the transport of particle patches in coastal environments.

Marine pollution bulletin
Several coastal regions require operational forecast systems for predicting the transport of pollutants released during marine accidents. In response to this need, surrogate models offer cost-effective solutions. Here, we propose a surrogate modeling...

Global greenhouse gas reduction forecasting via machine learning model in the scenario of energy transition.

Journal of environmental management
Global warming is becoming increasingly serious, with greenhouse gas (GHGs) emissions identified as a principal contributor. In response to the climate crisis, many countries are actively transitioning to renewable energy. Therefore, it is crucial to...

An interpretable (explainable) model based on machine learning and SHAP interpretation technique for mapping wind erosion hazard.

Environmental science and pollution research international
Soil erosion by wind poses a significant threat to various regions across the globe, such as drylands in the Middle East and Iran. Wind erosion hazard maps can assist in identifying the regions of highest wind erosion risk and are a valuable tool for...

A novel hybrid variable cross layer-based machine learning model improves the accuracy and interpretation of energy intensity prediction of wastewater treatment plant.

Journal of environmental management
Energy intensity (EI) prediction in wastewater treatment plants (WWTPs) suffers from inaccuracy and non-interpretability due to poor data quality, complex mechanisms and various confounding variables. In this study, the novel hybrid variable cross la...

Global forecasting of carbon concentration through a deep learning spatiotemporal modeling.

Journal of environmental management
Given the global urgency to mitigate climate change, a key action is the development of effective carbon concentration reduction policies. To this end, an influential factor is the availability of accurate predictions of carbon concentration trends. ...