AIMC Topic: Models, Theoretical

Clear Filters Showing 221 to 230 of 1953 articles

Dongting Lake algal bloom forecasting: Robustness and accuracy analysis of deep learning models.

Journal of hazardous materials
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...

Deanthropomorphising NLP: Can a language model be conscious?

PloS one
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...

Emulating Wildfire Plume Injection Using Machine Learning Trained by Large Eddy Simulation (LES).

Environmental science & technology
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...

Dynamics of infectious disease mathematical model through unsupervised stochastic neural network paradigm.

Computational biology and chemistry
The viruses has spread globally and have been impacted lives of people socially and economically, which causes immense suffering throughout the world. Thousands of people died and millions of illnesses were brought, by the outbreak worldwide. In orde...

A hybrid model for monthly runoff forecasting based on mixed signal processing and machine learning.

Environmental science and pollution research international
Monthly runoff forecasting plays a critically supportive role in water resources planning and management. Various signal decomposition techniques have been widely applied to enhance the accuracy of monthly runoff forecasting. However, the forecasting...

The research explores the predictive capacity of the shear strength of reinforced concrete walls with different cross-sectional shapes using the XGBoost model.

PloS one
Structurally, the lateral load-bearing capacity mainly depends on reinforced concrete (RC) walls. Determination of flexural strength and shear strength is mandatory when designing reinforced concrete walls. Typically, these strengths are determined t...

An integrated approach to a predictive and ranking model of use error using fuzzy BWM and fuzzy TOPSIS.

International journal of occupational safety and ergonomics : JOSE
Avoiding error in handling artifacts is crucial for achieving a high level of system reliability and safety assessment. This study develops a predictive and ranking model of use error (PRUE). In the first phase, use errors are systematically detected...

Medical language model specialized in extracting cardiac knowledge.

Scientific reports
The advent of the Transformer has significantly altered the course of research in Natural Language Processing (NLP) within the domain of deep learning, making Transformer-based studies the mainstream in subsequent NLP research. There has also been co...

An improved trajectory tracking control of quadcopter using a novel Sliding Mode Control with Fuzzy PID Surface.

PloS one
This paper presents Super Twisting Sliding Mode Control with a novel Fuzzy PID Surface for improved trajectory tracking of quadrotor unmanned aerial vehicles under external disturbances. First, quadrotor dynamic model with six degrees of freedom (6-D...

Construction of interpretable ensemble learning models for predicting bioaccumulation parameters of organic chemicals in fish.

Journal of hazardous materials
Accurate prediction of bioaccumulation parameters is essential for assessing exposure, hazards, and risks of chemicals. However, the majority of prediction models on bioaccumulation parameters are individual models based on a single algorithm and lac...