Comprehensive simulations are conducted both in single and multi-layer networks to investigate the learning performance of our algorithm, whose results demonstrate that our algorithm possesses higher learning e
Learning algorithms Machine Learning Skin cancer Statistical Learning References Skin Cancer Statistics: https://www.wcrf.org/dietandcancer/ cancer-trends/skincancer-statistics (2018) Rogers, H.W.; Weinstock, M.A.; Feldman, S.R.; Coldiron, B.M.: Incidence estimate of non-melanoma skin...
This effort also advances the application of Artificial Intelligence and Machine Learning (AI/ML) algorithms to the processing of radio frequency (RF) emitters, culminating in systems integration and flight demonstration in an open architecture pod in operationally representa...
The study may have been limited by sample size and sample representativeness, which may have affected the ability to generalize the results. A larger and more diverse sample may have contributed to the reliability and applicability of the study. In addition, machine learning algorithms, while excell...
Soft sensors, functioning as virtual instruments, utilize algorithms and computational models to estimate unobservable or impractical values by processing data derived from physical sensors [1,2]. In the Internet of Things (IoT) domain, where obtaining direct measurements can often be impractical or ec...
Explore related subjects Discover the latest articles and news from researchers in related subjects, suggested using machine learning. Learning algorithms Machine Learning Optimization Statistical Learning Algorithms Fire Science, Hazard Control, Building Safety ...
It can be seen that energy thresholds, template matching and machine learning algorithms have accomplished commendable work in the detection of bird sound. However, these methods are not inherently able to generalize to new conditions because of the limitations of background noise and differing species...
Data-driven algorithms provide advanced alternatives with statistical inference and machine learning techniques [6, 7]. In recent years, data-driven soft sensors including principal component regression (PCR), partial least squares (PLS) regression, support vector machine (SVM), extreme learning machine...
Afterward, making classification models using three machine-learning algorithms like K-Nearest Neighbour (KNN), Random Forest and Multilayer Perceptron (MLP), MLP is a type of the Artificial Neural Network (ANN) algorithm whereas KNN and Random Forest is a supervised type of algorithm....
Our proposed masquerade attack algorithms are mainly composed of a combination of perceptron learning and customized hill climbing algorithms. Experimental results show that our attack algorithms achieve very promising results where the best setting of our attack achieves 100% and 98.3% rank one ...