Artificial neural networks based optimization techniques: A review
In the last few years, intensive research has been done to enhance artificial intelligence (AI)
using optimization techniques. In this paper, we present an extensive review of artificial …
using optimization techniques. In this paper, we present an extensive review of artificial …
Systematic review of deep learning and machine learning for building energy
The building energy (BE) management plays an essential role in urban sustainability and
smart cities. Recently, the novel data science and data-driven technologies have shown …
smart cities. Recently, the novel data science and data-driven technologies have shown …
COVID-19 pandemic prediction for Hungary; a hybrid machine learning approach
Several epidemiological models are being used around the world to project the number of
infected individuals and the mortality rates of the COVID-19 outbreak. Advancing accurate …
infected individuals and the mortality rates of the COVID-19 outbreak. Advancing accurate …
Deep learning for detecting building defects using convolutional neural networks
Clients are increasingly looking for fast and effective means to quickly and frequently survey
and communicate the condition of their buildings so that essential repairs and maintenance …
and communicate the condition of their buildings so that essential repairs and maintenance …
Advances in machine learning modeling reviewing hybrid and ensemble methods
The conventional machine learning (ML) algorithms are continuously advancing and
evolving at a fast-paced by introducing the novel learning algorithms. ML models are …
evolving at a fast-paced by introducing the novel learning algorithms. ML models are …
Deep learning convolutional neural network in rainfall–runoff modelling
Rainfall–runoff modelling is complicated due to numerous complex interactions and
feedback in the water cycle among precipitation and evapotranspiration processes, and also …
feedback in the water cycle among precipitation and evapotranspiration processes, and also …
EEG based Major Depressive disorder and Bipolar disorder detection using Neural Networks: A review
Mental disorders represent critical public health challenges as they are leading contributors
to the global burden of disease and intensely influence social and financial welfare of …
to the global burden of disease and intensely influence social and financial welfare of …
A real-time apple targets detection method for picking robot based on ShufflenetV2-YOLOX
W Ji, Y Pan, B Xu, J Wang - Agriculture, 2022 - mdpi.com
In order to enable the picking robot to detect and locate apples quickly and accurately in the
orchard natural environment, we propose an apple object detection method based on …
orchard natural environment, we propose an apple object detection method based on …
Hybrid deep learning-based models for crop yield prediction
Predicting crop yield is a complex task since it depends on multiple factors. Although many
models have been developed so far in the literature, the performance of current models is …
models have been developed so far in the literature, the performance of current models is …
Deep learning and machine learning in hydrological processes climate change and earth systems a systematic review
Artificial intelligence methods and application have recently shown great contribution in
modeling and prediction of the hydrological processes, climate change, and earth systems …
modeling and prediction of the hydrological processes, climate change, and earth systems …