Convolutional neural networks (CNNs) have excelled in artificial intelligence, particularly in
image-related tasks such as classification and object recognition. However, manually …

An extensive examination of computational swarm intelligence reveals an escalating interest
in harnessing the capabilities of hybrid models and quantum-inspired algorithms with …

In recent years, the application of Data-Driven Models (DDMs) in ecological studies has
garnered significant attention due to their capacity to accurately simulate complex …

Computational intelligence (CI) techniques have developed very fast over the past two
decades, with many new methods emerging. Novel machine learning techniques, such as …

Autonomous vehicles have a number of open challenges, one of which is decision-making
regarding motion, particularly while operating in an environment that is both complex and …

Deep Learning and Enhanced Emissions Modeling and Deposition Prediction JCSIS
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Crop Yield Estimation Using Spiking Neural Networks Through Spatiotemporal Analysis of
Image Time Series JCSIS 019928311823 info@jcsis.org JCSIS About Volumes Instructions …

CNN-Based Algorithm for Anomaly Detection in Electrocardiogram Signals (BiLSTM) JCSIS
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In this paper, a multi-strategy fusion enhanced Honey Badger algorithm (EHBA) is proposed
to address the problem of easy convergence to local optima and difficulty in achieving fast …

This study presents a comprehensive evaluation of artificial neural networks (ANNs) for
predicting adiabatic compression heating in high-pressure processing (HPP) and high …