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Artificial intelligence for suspended sediment load prediction: a review
The estimation of sediment yield concentration is crucial for the development of stream
ventures, watershed management, toxins estimation, soil disintegration, floods, and so on. In …
ventures, watershed management, toxins estimation, soil disintegration, floods, and so on. In …
Monitoring the Industrial waste polluted stream-Integrated analytics and machine learning for water quality index assessment
Abstract The Water Quality Index (WQI) is a primary metric used to evaluate and categorize
surface water quality which plays a crucial role in the management of fresh water resources …
surface water quality which plays a crucial role in the management of fresh water resources …
Prediction of water quality indexes with ensemble learners: Bagging and boosting
One of the most crucial jobs to improve water resources management plans is the
assessment of river water quality. A water quality index (WQI) takes multiple water quality …
assessment of river water quality. A water quality index (WQI) takes multiple water quality …
Performance evaluation of concrete made with plastic waste using multi-expression programming
The immense production of plastic waste due to its non-biodegradable nature has become a
major issue for the world. Several researchers have recently tried to incorporate plastic …
major issue for the world. Several researchers have recently tried to incorporate plastic …
[HTML][HTML] Evolutionary and ensemble machine learning predictive models for evaluation of water quality
Abstract Study region Bisham Qilla and Doyian stations, Indus River Basin of Pakistan Study
focus Water pollution is an international concern that impedes human health, ecological …
focus Water pollution is an international concern that impedes human health, ecological …
Density-weighted support vector machines for binary class imbalance learning
In real-world binary classification problems, the entirety of samples belonging to each class
varies. These types of problems where the majority class is notably bigger than the minority …
varies. These types of problems where the majority class is notably bigger than the minority …
Water quality management using hybrid machine learning and data mining algorithms: An indexing approach
One of the key functions of global water resource management authorities is river water
quality (WQ) assessment. A water quality index (WQI) is developed for water assessments …
quality (WQ) assessment. A water quality index (WQI) is developed for water assessments …
Suspended sediment load prediction modelling based on artificial intelligence methods: The tropical region as a case study
The impact of the suspended sediment load (SSL) on environmental health, agricultural
operations, and water resources planning, is significant. The deposit of SSL restricts the …
operations, and water resources planning, is significant. The deposit of SSL restricts the …
An intuitionistic fuzzy kernel ridge regression classifier for binary classification
Kernel ridge regression (KRR) is a widely accepted efficient machine learning paradigm that
has been fruitfully implemented for solving both classification and regression problems. KRR …
has been fruitfully implemented for solving both classification and regression problems. KRR …
Affinity based fuzzy kernel ridge regression classifier for binary class imbalance learning
The class imbalance learning (CIL) problem indicates when one class have very low
proportions of samples (minority class) compared to the other class (majority class). Even …
proportions of samples (minority class) compared to the other class (majority class). Even …