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- research-article
Rotor fault characterisation in induction motors under different load levels via machine learning methods
International Journal of Artificial Intelligence and Soft Computing (IJAISC), Volume 8, Issue 22024, Pages 129–146https://doi.org/10.1504/ijaisc.2024.139606Induction motors stand out for their robustness and are widely used in the industrial sector. Literature studies have focused more on rotor faults because rotor fault signatures are hard to detect. In most experimental studies, tests were carried out ...
- retraction
- research-article
Effects of Histopathological Image Pre-processing on Convolutional Neural Networks
Procedia Computer Science (PROCS), Volume 132, Issue C2018, Pages 396–403https://doi.org/10.1016/j.procs.2018.05.166AbstractIn this study, classification performance of histopathological images which are processed by pre-processing algorithms using convolutional neural network structure is examined. The images are divided into four different pre-processing classes with ...
- research-article
Application of Feature Extraction and Classification Methods for Histopathological Image using GLCM, LBP, LBGLCM, GLRLM and SFTA
Procedia Computer Science (PROCS), Volume 132, Issue C2018, Pages 40–46https://doi.org/10.1016/j.procs.2018.05.057AbstractClassification of histopathologic images and identification of cancerous areas is quite challenging due to image background complexity and resolution. The difference between normal tissue and cancerous tissue is very small in some cases. So, the ...
- research-article
Riemann–Liouville fractional integral type exponential sampling Kantorovich series
Expert Systems with Applications: An International Journal (EXWA), Volume 238, Issue PFMar 2024https://doi.org/10.1016/j.eswa.2023.122350AbstractIn the present paper, we introduce a new family of sampling Kantorovich type operators using fractional-type integrals. We study approximation properties of newly constructed operators and give a rate of convergence via a suitable modulus of ...
Highlights- Exponential-type sampling series were introduced in the 1980s by optical physicists and engineers to study physically phenomena.
- research-article
- research-article
A new binary arithmetic optimization algorithm for uncapacitated facility location problem
Neural Computing and Applications (NCAA), Volume 36, Issue 8Mar 2024, Pages 4151–4177https://doi.org/10.1007/s00521-023-09261-xAbstractArithmetic Optimization Algorithm (AOA) is a heuristic method developed in recent years. The original version was developed for continuous optimization problems. Its success in binary optimization problems has not yet been sufficiently tested. In ...
- research-article
A new binary coati optimization algorithm for binary optimization problems
Neural Computing and Applications (NCAA), Volume 36, Issue 6Feb 2024, Pages 2797–2834https://doi.org/10.1007/s00521-023-09200-wAbstractThe coati optimization algorithm (COA) is a recently proposed heuristic algorithm. The COA algorithm, which solved the continuous optimization problems in its original paper, has been converted to a binary optimization solution by using transfer ...
- review-article
Metaverse token price forecasting using artificial neural networks (ANNs) and Adaptive neural fuzzy inference system (ANFIS)
Neural Computing and Applications (NCAA), Volume 36, Issue 7Mar 2024, Pages 3267–3290https://doi.org/10.1007/s00521-023-09228-yAbstractThis study is about the metaverse environment which has recently heard a lot in life. Although many individuals and institutions are interested in metaverse, it is an imaginary future space, and the conceptual framework is not fully drawn. The ...
- Article
Evaluation of Deep Learning Models for Lower Extremity Muscle Segmentation in Thermal Imaging
Artificial Intelligence over Infrared Images for Medical ApplicationsOct 2023, Pages 109–120https://doi.org/10.1007/978-3-031-44511-8_9AbstractCompetition and market size in sports are constantly increasing. In this case, one of the biggest problems of sports clubs is athlete injuries. Especially in football, athlete injury costs are very high. However, most injuries are non-contact and ...
- research-article
Singularly perturbed fuzzy initial value problems
Expert Systems with Applications: An International Journal (EXWA), Volume 223, Issue CAug 2023https://doi.org/10.1016/j.eswa.2023.119860AbstractIn this work, we have firstly introduced singularly perturbed fuzzy initial value problems (SPFIVPs) and then we have given an algorithm for the solutions of them by using the extension principle given by Zadeh. We have presented some results on ...
- research-article
Enhanced Coati Optimization Algorithm for Big Data Optimization Problem
Neural Processing Letters (NPLE), Volume 55, Issue 8Dec 2023, Pages 10131–10199https://doi.org/10.1007/s11063-023-11321-1AbstractThe recently proposed Coati Optimization Algorithm (COA) is one of the swarm-based intelligence algorithms. In this study, the current COA algorithm is developed and Enhanced COA (ECOA) is proposed. There is an imbalance between the exploitation ...
- research-article
Machine learning based detection of depression from task-based fMRI using weighted-3D-DWT denoising method
Multimedia Tools and Applications (MTAA), Volume 83, Issue 4Jan 2024, Pages 11805–11829https://doi.org/10.1007/s11042-023-15935-4AbstractDepression has become an important public health problem in recent years because the probability of a depressive episode in a person's entire life is generally between 18-20%. Neuroimaging techniques investigate diagnostic biomarkers in depression ...
- research-article
A comprehensive comparison of accuracy-based fitness functions of metaheuristics for feature selection
Soft Computing - A Fusion of Foundations, Methodologies and Applications (SOFC), Volume 27, Issue 13Jul 2023, Pages 8931–8958https://doi.org/10.1007/s00500-023-08414-3AbstractThe feature selection (FS) is a binary optimization problem in the discrete optimization problem category. Maximizing the accuracy by using fewer features is the main aim of FS. Metaheuristic algorithms are widely used for FS in literature. ...
- research-article
A novel adaptive memetic binary optimization algorithm for feature selection
Artificial Intelligence Review (ARTR), Volume 56, Issue 11Nov 2023, Pages 13463–13520https://doi.org/10.1007/s10462-023-10482-8AbstractFeature selection (FS) determines the beneficial features in data and decreases the disadvantages of the curse of dimensionality. This work proposes a novel adaptive memetic binary optimization (AMBO) algoraaithm for FS. FS is an NP-Hard binary ...