State-of-the-art review on energy and load forecasting in microgrids using artificial neural networks, machine learning, and deep learning techniques
Forecasting renewable energy efficiency significantly impacts system management and
operation because more precise forecasts mean reduced risk and improved stability and …
operation because more precise forecasts mean reduced risk and improved stability and …
Recent applications of AI to environmental disciplines: A review
A Konya, P Nematzadeh - Science of The Total Environment, 2024 - Elsevier
The rapid development and efficiency of Artificial Intelligence (AI) tools have made them
increasingly popular in various fields and research domains. The environmental discipline is …
increasingly popular in various fields and research domains. The environmental discipline is …
DCNNBT: A novel deep convolution neural network-based brain tumor classification model
An early brain tumor diagnosis is crucial for effective and proactive treatment, which
improves the patient's survival rate. In this paper, we propose a novel Deep Convolutional …
improves the patient's survival rate. In this paper, we propose a novel Deep Convolutional …
A lightweight object detection algorithm for remote sensing images based on attention mechanism and YOLOv5s
P Liu, Q Wang, H Zhang, J Mi, Y Liu - Remote Sensing, 2023 - mdpi.com
The specific characteristics of remote sensing images, such as large directional variations,
large target sizes, and dense target distributions, make target detection a challenging task …
large target sizes, and dense target distributions, make target detection a challenging task …
Imaging feature-based clustering of financial time series
J Wu, Z Zhang, R Tong, Y Zhou, Z Hu, K Liu - Plos one, 2023 - journals.plos.org
Timeseries representation underpin our ability to understand and predict the change of
natural system. Series are often predicated on our choice of highly redundant factors, and in …
natural system. Series are often predicated on our choice of highly redundant factors, and in …
Implementation of CNN for plant identification using UAV imagery
Plants are the world's most significant resource since they are the only natural source of
oxygen. Additionally, plants are considered crucial since they are the major source of energy …
oxygen. Additionally, plants are considered crucial since they are the major source of energy …
A risk prediction model for type 2 diabetes mellitus complicated with retinopathy based on machine learning and its application in health management
H Pan, J Sun, X Luo, H Ai, J Zeng, R Shi… - Frontiers in …, 2023 - frontiersin.org
Objective This study aimed to establish a risk prediction model for diabetic retinopathy (DR)
in the Chinese type 2 diabetes mellitus (T2DM) population using few inspection indicators …
in the Chinese type 2 diabetes mellitus (T2DM) population using few inspection indicators …
Intercomparing LSTM and RNN to a conceptual hydrological model for a low-land river with a focus on the flow duration curve
Machine learning (ML) algorithms slowly establish acceptance for the purpose of streamflow
modelling within the hydrological community. Yet, generally valid statements about the …
modelling within the hydrological community. Yet, generally valid statements about the …
Enhancing the conversational agent with an emotional support system for mental health digital therapeutics
As psychological diseases become more prevalent and are identified as the leading cause
of acquired disability, it is essential to assist people in improving their mental health. Digital …
of acquired disability, it is essential to assist people in improving their mental health. Digital …
A deep learning-based illumination transform for devignetting photographs of dermatological lesions
Photographs of skin lesions taken with standard digital cameras (macroscopic images) have
gained wide acceptance in dermatology. However, uneven background lighting caused by …
gained wide acceptance in dermatology. However, uneven background lighting caused by …