AIMC Topic: Models, Theoretical

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Coupling artificial neural network and sperm swarm optimization for soil temperature prediction at multiple depths.

Environmental science and pollution research international
Soil temperature (ST) stands as a pivotal parameter in the realm of water resources and irrigation. It serves as a guide for farmers, enabling them to determine optimal planting and fertilization timings. In the backdrop of regions like Iran, where w...

Coagulo-Net: Enhancing the mathematical modeling of blood coagulation using physics-informed neural networks.

Neural networks : the official journal of the International Neural Network Society
Blood coagulation, which involves a group of complex biochemical reactions, is a crucial step in hemostasis to stop bleeding at the injury site of a blood vessel. Coagulation abnormalities, such as hypercoagulation and hypocoagulation, could either c...

Touchformer: A Transformer-Based Two-Tower Architecture for Tactile Temporal Signal Classification.

IEEE transactions on haptics
Haptic temporal signal recognition plays an important supporting role in robot perception. This paper investigates how to improve classification performance on multiple types of haptic temporal signal datasets using a Transformer model structure. By ...

Co-firing characteristic prediction of solid waste and coal for supercritical CO power cycle based on CFD simulation and machine learning algorithm.

Waste management (New York, N.Y.)
The co-firing technology of combustible solid waste (CSW) and coal in the supercritical CO (S-CO) circulating fluidized bed (CFB) can effectively deal with domestic waste, promote social and environmental benefits, improve the coal conversion rate, a...

A predictive fuzzy logic and rule-based control approach for practical real-time operation of urban stormwater storage system.

Water research
Predictive real-time control (RTC) strategies are usually more effective than reactive strategies for the intelligent management of urban stormwater storage systems. However, it remains a challenge to ensure the practicality of RTC strategies that us...

Transferable and data efficient metamodeling of storm water system nodal depths using auto-regressive graph neural networks.

Water research
Storm water systems (SWSs) are essential infrastructure providing multiple services including environmental protection and flood prevention. Typically, utility companies rely on computer simulators to properly design, operate, and manage SWSs. Howeve...

An intrusion detection model to detect zero-day attacks in unseen data using machine learning.

PloS one
In an era marked by pervasive digital connectivity, cybersecurity concerns have escalated. The rapid evolution of technology has led to a spectrum of cyber threats, including sophisticated zero-day attacks. This research addresses the challenge of ex...

Spatial prediction of groundwater salinity in multiple aquifers of the Mekong Delta region using explainable machine learning models.

Water research
Groundwater salinization is a prevalent issue in coastal regions, yet accurately predicting and understanding its causal factors remains challenging due to the complexity of the groundwater system. Therefore, this study predicted groundwater salinity...

Application and innovation of artificial intelligence models in wastewater treatment.

Journal of contaminant hydrology
At present, as the problem of water shortage and pollution is growing serious, it is particularly important to understand the recycling and treatment of wastewater. Artificial intelligence (AI) technology is characterized by reliable mapping of nonli...

Analysis of coupling in geographic information systems based on WASPAS method for bipolar complex fuzzy linguistic Aczel-Alsina power aggregation operators.

PloS one
The model of bipolar complex fuzzy linguistic set is a very famous and dominant principle to cope with vague and uncertain information. The bipolar complex fuzzy linguistic set contained the positive membership function, negative membership function,...