Forecasting renewable energy generation with machine learning and deep learning: Current advances and future prospects
This article presents a review of current advances and prospects in the field of forecasting
renewable energy generation using machine learning (ML) and deep learning (DL) …
renewable energy generation using machine learning (ML) and deep learning (DL) …
Fuzzy logic approach for infectious disease diagnosis: A methodical evaluation, literature and classification
This paper presents a systematic review of the literature and the classification of fuzzy logic
application in an infectious disease. Although the emergence of infectious diseases and …
application in an infectious disease. Although the emergence of infectious diseases and …
Diagnosing of disease using machine learning
The role of machine learning in the healthcare industry is inevitable due to its power to use
in disease detection and management. Disease diagnosis using machine-learning …
in disease detection and management. Disease diagnosis using machine-learning …
Classification of COVID-19 individuals using adaptive neuro-fuzzy inference system
Coronavirus is a fatal disease that affects mammals and birds. Usually, this virus spreads in
humans through aerial precipitation of any fluid secreted from the infected entity's body part …
humans through aerial precipitation of any fluid secreted from the infected entity's body part …
An augmented artificial intelligence approach for chronic diseases prediction
J Rashid, S Batool, J Kim, M Wasif Nisar… - Frontiers in Public …, 2022 - frontiersin.org
Chronic diseases are increasing in prevalence and mortality worldwide. Early diagnosis has
therefore become an important research area to enhance patient survival rates. Several …
therefore become an important research area to enhance patient survival rates. Several …
Preference learning for eco-friendly hotels recommendation: A multi-criteria collaborative filtering approach
The crucial role of customers' positive experience and their subsequent word-of-mouth have
been highlighted by both scholars and practitioners for all industry sectors. In response to an …
been highlighted by both scholars and practitioners for all industry sectors. In response to an …
Predicting parkinson's disease progression: Evaluation of ensemble methods in machine learning
M Nilashi, RA Abumalloh… - Journal of healthcare …, 2022 - Wiley Online Library
Parkinson's disease (PD) is a complex neurodegenerative disease. Accurate diagnosis of
this disease in the early stages is crucial for its initial treatment. This paper aims to present a …
this disease in the early stages is crucial for its initial treatment. This paper aims to present a …
Intelligent monitoring for infectious diseases with fuzzy systems and edge computing: A survey
Q Jiang, X Zhou, R Wang, W Ding, Y Chu, S Tang… - Applied Soft …, 2022 - Elsevier
Infectious diseases usually have the characteristics of rapid spread with a large impact
range. Once they break out, they will cause a large area of infection, which creates …
range. Once they break out, they will cause a large area of infection, which creates …
[HTML][HTML] Medical disease analysis using neuro-fuzzy with feature extraction model for classification
Medical disease classification using machine learning algorithms is a challenging task due
to the nature of data, which can contain incomplete, uncertain, and imprecise information …
to the nature of data, which can contain incomplete, uncertain, and imprecise information …
Remote tracking of Parkinson's disease progression using ensembles of deep belief network and self-organizing map
Parkinson's Disease (PD) is one of the most prevalent neurological disorders characterized
by impairment of motor function. Early diagnosis of PD is important for initial treatment. This …
by impairment of motor function. Early diagnosis of PD is important for initial treatment. This …