A review of the artificial neural network models for water quality prediction
Water quality prediction plays an important role in environmental monitoring, ecosystem
sustainability, and aquaculture. Traditional prediction methods cannot capture the nonlinear …
sustainability, and aquaculture. Traditional prediction methods cannot capture the nonlinear …
Application of machine learning in intelligent fish aquaculture: A review
Among the background of developments in automation and intelligence, machine learning
technology has been extensively applied in aquaculture in recent years, providing a new …
technology has been extensively applied in aquaculture in recent years, providing a new …
[HTML][HTML] A novel hybrid BPNN model based on adaptive evolutionary Artificial Bee Colony Algorithm for water quality index prediction
L Chen, T Wu, Z Wang, X Lin, Y Cai - Ecological Indicators, 2023 - Elsevier
With the accelerated industrialization and urbanization process, water pollution in rivers is
being increasingly worsened, and has caused a series of ecological and environmental …
being increasingly worsened, and has caused a series of ecological and environmental …
Deep learning for smart fish farming: applications, opportunities and challenges
The rapid emergence of deep learning (DL) technology has resulted in its successful use in
various fields, including aquaculture. DL creates both new opportunities and a series of …
various fields, including aquaculture. DL creates both new opportunities and a series of …
Prediction and control of water quality in Recirculating Aquaculture System based on hybrid neural network
J Yang, L Jia, Z Guo, Y Shen, X Li, Z Mou, K Yu… - … Applications of Artificial …, 2023 - Elsevier
Abstract In the Recirculating Aquaculture Systems (RAS), the control of water quality indices
remains essential to survival and growth of aquaculture objects. This requires effect …
remains essential to survival and growth of aquaculture objects. This requires effect …
Evaluation of fish feeding intensity in aquaculture using a convolutional neural network and machine vision
In aquaculture, information on fish appetite is of great significance for guiding feeding and
production practices. However, most fish appetite assessment methods are inefficient and …
production practices. However, most fish appetite assessment methods are inefficient and …
[HTML][HTML] Internet of Things in aquaculture: A review of the challenges and potential solutions based on current and future trends
Aquaculture produces nearly half of the seafood consumed by the ever-growing world
population. There have been attempts to adopt novel technologies into the industry to …
population. There have been attempts to adopt novel technologies into the industry to …
[HTML][HTML] Overview of smart aquaculture system: Focusing on applications of machine learning and computer vision
Smart aquaculture is nowadays one of the sustainable development trends for the
aquaculture industry in intelligence and automation. Modern intelligent technologies have …
aquaculture industry in intelligence and automation. Modern intelligent technologies have …
Using convolutional neural network for predicting cyanobacteria concentrations in river water
Abstract Machine learning modeling techniques have emerged as a potential means for
predicting algal blooms. In this study, synthetic spatio-temporal water quality data for a river …
predicting algal blooms. In this study, synthetic spatio-temporal water quality data for a river …
Recent advances of smart systems and internet of things (iot) for aquaponics automation: A comprehensive overview
Aquaponics is an innovative, smart, and sustainable agricultural technology that integrates
aquaculture (farming of fish) with hydroponics in growing vegetable crops symbiotically. The …
aquaculture (farming of fish) with hydroponics in growing vegetable crops symbiotically. The …