AIMC Topic: Whales

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PM concentration prediction using a whale optimization algorithm based hybrid deep learning model in Beijing, China.

Environmental pollution (Barking, Essex : 1987)
PM is a significant global atmospheric pollutant impacting visibility, climate, and public health. Accurate prediction of PM concentrations is critical for assessing air pollution risks and providing early warnings for effective management. This stud...

Optimizing Kernel Extreme Learning Machine based on a Enhanced Adaptive Whale Optimization Algorithm for classification task.

PloS one
Data classification is an important research direction in machine learning. In order to effectively handle extensive datasets, researchers have introduced diverse classification algorithms. Notably, Kernel Extreme Learning Machine (KELM), as a fast a...

Fractional whale driving training-based optimization enabled transfer learning for detecting autism spectrum disorder.

Computational biology and chemistry
Autism Spectrum Disorder (ASD) is a neurological illness that degrades communication and interaction among others. Autism can be detected at any stage. Early detection of ASD is important in preventing the communication, interaction and behavioral ou...

Machine learning with taxonomic family delimitation aids in the classification of ephemeral beaked whale events in passive acoustic monitoring.

PloS one
Passive acoustic monitoring is an essential tool for studying beaked whale populations. This approach can monitor elusive and pelagic species, but the volume of data it generates has overwhelmed researchers' ability to quantify species occurrence for...

Debris flow volume prediction model based on back propagation neural network optimized by improved whale optimization algorithm.

PloS one
Debris flow is a sudden natural disaster in mountainous areas, which seriously threatens the lives and property of nearby residents. Therefore, it is necessary to predict the volume of debris flow accurately and reliably. However, the predictions of ...

CO-WOA: Novel Optimization Approach for Deep Learning Classification of Fish Image.

Chemistry & biodiversity
The most significant groupings of cold-blooded creatures are the fish family. It is crucial to recognize and categorize the most significant species of fish since various species of seafood diseases and decay exhibit different symptoms. Systems based...

DISCO: A deep learning ensemble for uncertainty-aware segmentation of acoustic signals.

PloS one
Recordings of animal sounds enable a wide range of observational inquiries into animal communication, behavior, and diversity. Automated labeling of sound events in such recordings can improve both throughput and reproducibility of analysis. Here, we...

Classification of Marine Mammals Using the Trained Multilayer Perceptron Neural Network with the Whale Algorithm Developed with the Fuzzy System.

Computational intelligence and neuroscience
The existence of various sounds from different natural and unnatural sources in the deep sea has caused the classification and identification of marine mammals intending to identify different endangered species to become one of the topics of interest...

A novel model based on CEEMDAN, IWOA, and LSTM for ultra-short-term wind power forecasting.

Environmental science and pollution research international
The randomness and instability of wind power bring challenges to power grid dispatching. Accurate prediction of wind power is significant to ensure the stable development of power grid. In this paper, a new ultra-short-term wind power forecasting mod...

Integrated Prediction Framework for Clinical Scores of Cognitive Functions in ESRD Patients.

Computational intelligence and neuroscience
The clinical scores are applied to determine the stage of cognitive function in patients with end-stage renal disease (ESRD). However, accurate clinical scores are hard to come by. This paper proposed an integrated prediction framework with GPLWLSV t...