AIMC Topic:
Computer Simulation

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Implementation and Optimization of Reverse Suspension Structure Design Model Using Deep Learning.

Computational intelligence and neuroscience
The present work aims to improve the design efficiency and optimize the results in the increasingly complex and diversified material design projects to help architects realize the better performance of building structures. According to the characteri...

Granger causality test with nonlinear neural-network-based methods: Python package and simulation study.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Causality defined by Granger in 1969 is a widely used concept, particularly in neuroscience and economics. As there is an increasing interest in nonlinear causality research, a Python package with a neural-network-based caus...

A Graph Neural Network Based Decentralized Learning Scheme.

Sensors (Basel, Switzerland)
As an emerging paradigm considering data privacy and transmission efficiency, decentralized learning aims to acquire a global model using the training data distributed over many user devices. It is a challenging problem since link loss, partial devic...

Construction of computer model for enterprise green innovation by PSO-BPNN algorithm and its impact on economic performance.

PloS one
The present work aims to analyze the elements that affect corporate green technology innovation and investigate a method suitable for predicting and evaluating corporate performance. First, the elements of green technology innovation and their relati...

Interpretation of Structure-Activity Relationships in Real-World Drug Design Data Sets Using Explainable Artificial Intelligence.

Journal of chemical information and modeling
In silico models based on Deep Neural Networks (DNNs) are promising for predicting activities and properties of new molecules. Unfortunately, their inherent black-box character hinders our understanding, as to which structural features are important ...

A novel hybrid soft computing optimization framework for dynamic economic dispatch problem of complex non-convex contiguous constrained machines.

PloS one
The reformations of the electrical power sector have resulted in very dynamic and competitive market that has changed many elements of the power industry. Excessive demand of energy, depleting the fossil fuel reserves of planet and releasing the toxi...

AIME: Autoencoder-based integrative multi-omics data embedding that allows for confounder adjustments.

PLoS computational biology
In the integrative analyses of omics data, it is often of interest to extract data representation from one data type that best reflect its relations with another data type. This task is traditionally fulfilled by linear methods such as canonical corr...

Service Level Agreement Monitoring as a Service: An Independent Monitoring Service for Service Level Agreements in Clouds.

Big data
The cloud network is rapidly growing due to a massive increase in interconnected devices and the emergence of different technologies such as the Internet of things, fog computing, and artificial intelligence. In response, cloud computing needs reliab...

Deep learning model inspired by lateral line system for underwater object detection.

Bioinspiration & biomimetics
Inspired by the lateral line systems of various aquatic organisms that are capable of hydrodynamic imaging using ambient flow information, this study develops a deep learning-based object localization model that can detect the location of objects usi...

Research on the Communication Strategy of History and Culture in Shaanxi Based on BP Neural Network Model.

Computational intelligence and neuroscience
Shaanxi is one of China's most important cradles of civilization. The main vein of Chinese culture is rich history and culture, and brilliant red culture embodies the essence of socialist core values. It is still relatively weak to deeply analyze the...