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Multi-input CNN based vibro-acoustic fusion for accurate fault diagnosis of induction motor
Induction motor (IM) is a highly efficient prime mover in industrial applications. To maintain
an uninterrupted operation, accurate fault diagnosis system of IM is required. It can help to …
an uninterrupted operation, accurate fault diagnosis system of IM is required. It can help to …
[HTML][HTML] Hybrid CNN and XGBoost model tuned by modified arithmetic optimization algorithm for COVID-19 early diagnostics from X-ray images
Develo** countries have had numerous obstacles in diagnosing the COVID-19 worldwide
pandemic since its emergence. One of the most important ways to control the spread of this …
pandemic since its emergence. One of the most important ways to control the spread of this …
Augmented weighted K-means grey wolf optimizer: An enhanced metaheuristic algorithm for data clustering problems
This study presents the K-means clustering-based grey wolf optimizer, a new algorithm
intended to improve the optimization capabilities of the conventional grey wolf optimizer in …
intended to improve the optimization capabilities of the conventional grey wolf optimizer in …
Breast cancer diagnosis using support vector machine optimized by improved quantum inspired grey wolf optimization
A prompt diagnosis of breast cancer in its earliest phases is necessary for effective
treatment. While Computer-Aided Diagnosis systems play a crucial role in automated …
treatment. While Computer-Aided Diagnosis systems play a crucial role in automated …
Software defects prediction by metaheuristics tuned extreme gradient boosting and analysis based on shapley additive explanations
Software testing represents a crucial component of software development, and it is usually
making the difference between successful and failed projects. Although it is extremely …
making the difference between successful and failed projects. Although it is extremely …
Metaheuristic-based hyperparameter tuning for recurrent deep learning: application to the prediction of solar energy generation
As solar energy generation has become more and more important for the economies of
numerous countries in the last couple of decades, it is highly important to build accurate …
numerous countries in the last couple of decades, it is highly important to build accurate …
[HTML][HTML] Application of natural language processing and machine learning boosted with swarm intelligence for spam email filtering
Spam represents a genuine irritation for email users, since it often disturbs them during their
work or free time. Machine learning approaches are commonly utilized as the engine of …
work or free time. Machine learning approaches are commonly utilized as the engine of …
Employing machine learning for enhanced abdominal fat prediction in cavitation post-treatment
This study investigates the application of cavitation in non-invasive abdominal fat reduction
and body contouring, a topic of considerable interest in the medical and aesthetic fields. We …
and body contouring, a topic of considerable interest in the medical and aesthetic fields. We …
Optimizing long-short-term memory models via metaheuristics for decomposition aided wind energy generation forecasting
Power supply from renewable energy is an important part of modern power grids. Robust
methods for predicting production are required to balance production and demand to avoid …
methods for predicting production are required to balance production and demand to avoid …
[HTML][HTML] Forecasting bitcoin: Decomposition aided long short-term memory based time series modeling and its explanation with Shapley values
Bitcoin price volatility fascinates both researchers and investors, studying features that
influence its movement. This paper expends on previous research and examines time series …
influence its movement. This paper expends on previous research and examines time series …