AIMC Topic: Models, Theoretical

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Utilizing InVEST ecosystem services model combined with deep learning and fallback bargaining for effective sediment retention in Northern Iran.

Environmental science and pollution research international Dec 14, 2024
This study aimed to integrate game theory and deep learning algorithms with the InVEST Ecosystem Services Model (IESM) for Sediment Retention (SR) modeling in the Kasilian watershed, Iran. The Kasilian watershed is characterized by multiple sub-water...
Geologic Sediments Models, Theoretical Iran Algorithms Ecosystem Deep Learning
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A novel strategy for the MPPT in a photovoltaic system via sliding modes control.

PloS one Dec 13, 2024
This paper proposes a robust maximum power point tracking algorithm based on a super twisting sliding modes controller. The underlying idea is solving the classical trajectory tracking control problem where the maximum power point defines the referen...
Electric Power Supplies Temperature Bayes Theorem Models, Theoretical Algorithms Neural Networks, Computer Solar Energy Computer Simulation
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Towards A universal settling model for microplastics with diverse shapes: Machine learning breaking morphological barriers.

Water research Dec 12, 2024
Accurately predicting the settling velocity of microplastics in aquatic environments is a prerequisite for reliably modeling their transport processes. An increasing number of settling models have been proposed for microplastics with fragmented, film...
Water Pollutants, Chemical Machine Learning Microplastics Models, Theoretical
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Plane coexistence behaviors for Hopfield neural network with two-memristor-interconnected neurons.

Neural networks : the official journal of the International Neural Network Society Dec 12, 2024
Memristors are commonly used as the connecting parts of neurons in brain-like neural networks. The memristors, unlike the existing literature, possess the capability to function as both self-connected synaptic weights and interconnected synaptic weig...
Models, Theoretical Hopfield Neural Networks
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A hybrid deep learning model based on signal decomposition and dynamic feature selection for forecasting the influent parameters of wastewater treatment plants.

Environmental research Dec 12, 2024
Accurate prediction of influent parameters such as chemical oxygen demand (COD) and biochemical oxygen demand over five days (BOD) is crucial for optimizing wastewater treatment processes, enhancing efficiency, and reducing costs. Traditional predict...
Biological Oxygen Demand Analysis Waste Disposal, Fluid Models, Theoretical Deep Learning Wastewater Forecasting
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Advanced susceptibility analysis of ground deformation disasters using large language models and machine learning: A Hangzhou City case study.

PloS one Dec 12, 2024
To address the prevailing scenario where comprehensive susceptibility assessments of ground deformation disasters primarily rely on knowledge-driven models, with weight judgments largely founded on expert subjective assessments, this study initially ...
Humans Disasters Neural Networks, Computer Models, Theoretical China Machine Learning Language Cities
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Development of multistage crop yield estimation model using machine learning and deep learning techniques.

International journal of biometeorology Dec 7, 2024
In this research paper, machine learning techniques were applied to a multivariate meteorological time series data for estimating the wheat yield of five districts of Punjab. Wheat yield data and weather parameters over 34 years were collected from t...
Weather Crops, Agricultural Models, Theoretical Triticum Neural Networks, Computer Machine Learning Deep Learning India
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Dongting Lake algal bloom forecasting: Robustness and accuracy analysis of deep learning models.

Journal of hazardous materials Dec 5, 2024
Harmful algal blooms (HABs) pose a significant threat to aquatic ecosystems, prompting efforts to predict their occurrence for swift action by water management agencies. Despite the potential for high-precision forecasting through machine learning, t...
Forecasting China Models, Theoretical Lakes Deep Learning Water Quality Environmental Monitoring Harmful Algal Bloom
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Deanthropomorphising NLP: Can a language model be conscious?

PloS one Dec 4, 2024
This work is intended as a voice in the discussion over previous claims that a pretrained large language model (LLM) based on the Transformer model architecture can be sentient. Such claims have been made concerning the LaMDA model and also concernin...
Language Models, Theoretical Natural Language Processing Consciousness Humans
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Emulating Wildfire Plume Injection Using Machine Learning Trained by Large Eddy Simulation (LES).

Environmental science & technology Dec 3, 2024
Wildfires have a major influence on the Earth system, with costly impacts on society. Despite decades of research, wildfires are still challenging to represent in air quality and chemistry-climate models. Wildfire plume rise (injection) is one of tho...
Air Pollution Wildfires Machine Learning Models, Theoretical
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