AIMC Topic: Models, Theoretical

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Trajectory tracking and obstacle avoidance in dynamic environments using an improved artificial potential field method.

PloS one
Ensuring that a robot employing demonstration learning models can simultaneously achieve accurate trajectory tracking of demonstrated paths and effective avoidance of moving obstacles in dynamic environments remains a critical research challenge. Thi...

Multi-objective production scheduling optimization strategy based on fuzzy mathematics theory.

PloS one
Multi-objective production scheduling faces the problems of inter-objective conflicts, many uncertainty factors and the difficulty of traditional optimization algorithms to deal with complexity and ambiguity, and there is an urgent need to introduce ...

Consensus stability among composite decision makers in the framework of hesitant fuzzy graph model with application to doctor-patient disputes.

Scientific reports
Doctor-patient disputes are inevitable in human beings' social lives. The rapid development of social media makes doctor-patient disputes easier to spiral out of control. One of the ensuing problems is that the size of the parties in conflict has inc...

Simulation of emitter discharge along drip laterals under drip fertigation system using artificial neural network.

PloS one
Simulation of emitter discharge under a drip fertigation system is important for capturing the variation in water and nutrient distribution to crops. This is important for an effective design and irrigation management for agricultural crops. Moreover...

Using open data to derive parsimonious data-driven models for uncovering the influence of local traffic and meteorology on air quality: The case of Madrid.

Environmental pollution (Barking, Essex : 1987)
Air pollution remains a critical public health and environmental challenge, particularly in urban areas where traffic emissions and meteorological conditions strongly influence air quality. While Machine Learning (ML) techniques have been increasingl...

A Bayesian Maximum Entropy Fusion model for enhanced prediction and risk assessment of fluoride and arsenic contamination in groundwater.

Journal of contaminant hydrology
In the central and western regions of Jilin Province, excessive groundwater extraction has resulted in elevated levels of fluoride (F) and arsenic (As) in drinking water. Prolonged exposure to these contaminants is linked to endemic health issues, in...

Double reinforcement learning for cluster synchronization of Boolean control networks under denial of service attacks.

PloS one
This paper investigates the asymptotic cluster synchronization of Boolean control networks (BCNs) under denial-of-service (DoS) attacks, where each state node in the network experiences random data loss following a Bernoulli distribution. First, the ...

The effectiveness of explainable AI on human factors in trust models.

Scientific reports
Explainable AI has garnered significant traction in science communication research. Prior empirical studies have firmly established that explainable AI communication could improve trust in AI and that trust in AI engineers was argued to be an under-e...

Monitoring and predicting cotton leaf diseases using deep learning approaches and mathematical models.

Scientific reports
Cotton, the backbone of global textile production, demands sustainable agricultural practices to ensure fiber, food, and environmental security. Cotton crop play an essential role in farming economies; however, production is sometimes affected by var...

Cognition-enhanced geospatial decision framework integrating fuzzy FCA, surprisingly popular method, and a large language model.

Scientific reports
This study introduces a cognition-enhanced framework for geospatial decision-making by integrating Fuzzy Formal Concept Analysis (FCA), the Surprisingly Popular (SP) method, and a Large Language Model (GPT-4o). Our approach captures cognitive influen...