AIMC Topic: Computer Simulation

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Support Vector Regression for Mobile Target Localization in Indoor Environments.

Sensors (Basel, Switzerland)
Trilateration-based target localization using received signal strength (RSS) in a wireless sensor network (WSN) generally yields inaccurate location estimates due to high fluctuations in RSS measurements in indoor environments. Improving the localiza...

A machine learning-driven approach for prioritizing food contact chemicals of carcinogenic concern based on complementary in silico methods.

Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association
Carcinogenicity is one of the most critical endpoints for the risk assessment of food contact chemicals (FCCs). However, the carcinogenicity of FCCs remains insufficiently investigated. To fill the data gap, the application of standard experimental m...

Application of Optimized GA-BPNN Algorithm in English Teaching Quality Evaluation System.

Computational intelligence and neuroscience
The assessment of teaching quality is a very complex and fuzzy nonlinear process, which involves many factors and variables, so the establishment of the mathematical model is complicated, and the traditional evaluation method of teaching quality is n...

Online public opinion evaluation through the functional resonance analysis method and deep analysis.

PloS one
A conventional model of public opinion analysis is no longer suitable when the internet is the primary arena of information dissemination. Thus, a more practical approach is urgently needed to deal with this dynamic and complicated phenomenon of prop...

Robust and Secure Data Transmission Using Artificial Intelligence Techniques in Ad-Hoc Networks.

Sensors (Basel, Switzerland)
The paper presents a new security aspect for a Mobile Ad-Hoc Network (MANET)-based IoT model using the concept of artificial intelligence. The Black Hole Attack (BHA) is considered one of the most affecting threats in the MANET in which the attacker ...

Observer-based adaptive neural tracking control for a class of nonlinear systems with prescribed performance and input dead-zone constraints.

Neural networks : the official journal of the International Neural Network Society
This paper investigates the problem of output feedback neural network (NN) learning tracking control for nonlinear strict feedback systems subject to prescribed performance and input dead-zone constraints. First, an NN is utilized to approximate the ...

Dynamic Space Allocation Based on Internal Demand for Optimizing Release of Shared Parking.

Sensors (Basel, Switzerland)
The size of cities has been continuously increasing because of urbanization. The number of public and private transportation vehicles is rapidly increasing, thus resulting in traffic congestion, traffic accidents, and environmental pollution. Althoug...

The automatic parameter-exploration with a machine-learning-like approach: Powering the evolutionary modeling on the origin of life.

PLoS computational biology
The origin of life involved complicated evolutionary processes. Computer modeling is a promising way to reveal relevant mechanisms. However, due to the limitation of our knowledge on prebiotic chemistry, it is usually difficult to justify parameter-s...

Underwater gliders linear trajectory tracking: The experience breeding actor-critic approach.

ISA transactions
This paper studies the underwater glider trajectory tracking in currents field. The objective is to ensure that trajectories fit to the straight target track. The underwater glider model is introduced to demonstrate the vehicle dynamic properties. Co...

Online machine learning algorithms to optimize performances of complex wireless communication systems.

Mathematical biosciences and engineering : MBE
Data-driven and feedback cycle-based approaches are necessary to optimize the performance of modern complex wireless communication systems. Machine learning technologies can provide solutions for these requirements. This study shows a comprehensive f...