Classification of skin cancer stages using a AHP fuzzy technique within the context of big data healthcare

Samiei, Moslem; Hassani, Alireza; Sarspy, Sliva; Komari, Iraj Elyasi; Trik, Mohammad; Hassanpour, Foad

doi:10.1007/s00432-023-04815-x

Cited by 27 publications

(11 citation statements)

References 60 publications

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“…According to [32], the phasor computations are finished in 21.38 ms, and the PMU utilized to carry out the DFT method needs less than 150 m. Serially over a period of 22‐ms intervals, up to a maximum of 30 factors, the phasors in the measurement channels are computed in line with the IEEE C37.118 standard [33, 34]. This limitation ensures the accuracy of other tasks completed within a second, such as the measurement of active, reactive, and apparent power, the calculation of RMS voltage and current, and the localization of the source of electrical disturbances with the help of the proposed fuzzy algorithm.…”

Section: Suggested Methodsmentioning

confidence: 99%

Diagnosis and classification of disturbances in the power distribution network by phasor measurement unit based on fuzzy intelligent system

Khosravi,

Trik,

Ansari

2024

The Journal of Engineering

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The dynamic nature of distribution networks raises fresh issues with how such electrical systems function. These networks have some characteristics that indicate the need for better monitoring and control capabilities, including dispersed generation employing renewable resources, changing load profiles, and rising reliability requirements. Phasor measurement units (PMUs) offer simultaneous voltage and current phasor measurements at various places and offer a variety of options for gauging the condition and health of the power distribution network. In this regard, a cost‐optimized PMU with some unique features for distribution systems is presented in this work. These features include a fuzzy inference system to determine the root cause of potential electrical disturbances and methods to estimate electrical parameters through measured field data, which are necessities. This study takes into account the modelling of PMUs, utilizing a process for fault detection and classification with a fuzzy inference network. The 9‐bus distribution network's dependability model is built once the components and their functions are first outlined. The proposed model is then used to calculate the availability of the presented model, which has been examined to provide an analogous reliability model for PMUs. Depending on the specific manufacturer, the PMU's design and specs will change. To extract phase and size measurement features for the proposed model adaptive neural‐fuzzy inference system network's training, two PMU structures and associated reliability models are described here. When merging input data for fuzzy neural network prediction using MATLAB software, fuzzy sets are taken into account for error classification analysis.

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Section: Suggested Methodsmentioning

confidence: 99%

Diagnosis and classification of disturbances in the power distribution network by phasor measurement unit based on fuzzy intelligent system

Khosravi,

Trik,

Ansari

2024

The Journal of Engineering

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“… Purpose Method Parameters Advantages Disadvantages [ 19 ] Cardiovascular disease prognosis Incorporating techniques from both machine learning and data mining precision Coordinate data from multiple sources and spot trends quickly. Challenges in data interpretation and heightened susceptibility to bias [ 20 ] Cardiovascular disease prognosis Chi-square and principal component analysis for cardiac disease diagnosis precision The method's simplicity and ease of use It does poorly when used on a collection of features that are dependent on one another. [ 40 ] Cardiovascular disease prognosis Heart disease can be identified using a variety of classification techniques and a set of ideal criteria.…”

Section: Related Workmentioning

confidence: 99%

“…Nearly all physicians utilize knowledge and experience to foresee cardiac illness. In the field of medicine, figuring out the cause of an illness is difficult and time-consuming [ 19 , 20 ]. Heart disease prediction is a complicated subject that could result in erroneous assumptions and undesired outcomes.…”

Section: Introductionmentioning

confidence: 99%

An optimal method for diagnosing heart disease using combination of grasshopper evalutionary algorithm and support vector machines

Zhou,

Liu,

Zhou

et al. 2024

Heliyon

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“…It should be noted that the word codes can be used to determine the mixture ratio of the document surface. The variable is used in (2) [20] to indicate the contribution vector of the k th title in the document w.…”

Section: B Coding Of Thin Group Topicmentioning

confidence: 99%

A New Method for Revealing Traffic Patterns in Video Surveillance using a Topic Model

Wang

2023

IJACSA

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Research on video surveillance systems, for instance, in intelligent transportation systems, has advanced due to the growing requirement for monitoring, control, and intelligent management. One of the next issues is extracting patterns and automatically classifying them, given the volume of data produced by these systems. In this study, a theme approach was utilized to translate visual patterns into visual words in order to reveal and extract traffic patterns at crossings. The supplied video is first cut up into segments. The optical flux technique is then used to determine the clips' optical flux characteristics, which are based on a lot of local motion vector data, and translate them into visual words. The thin-group thematic coding method is then used to teach traffic patterns to the proposed system using a non-probable thematic model. By responding to a behavioral query like "Where is a vehicle going?" these patterns convey observable motion that can be utilized to characterize a scene. The results of applying the suggested method to the QM_UL video database demonstrated that the suggested method can accurately identify and depict significant traffic patterns such as left turns, right turns, and intersection crossings.

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Classification of skin cancer stages using a AHP fuzzy technique within the context of big data healthcare

Cited by 27 publications

References 60 publications

Diagnosis and classification of disturbances in the power distribution network by phasor measurement unit based on fuzzy intelligent system

Diagnosis and classification of disturbances in the power distribution network by phasor measurement unit based on fuzzy intelligent system

An optimal method for diagnosing heart disease using combination of grasshopper evalutionary algorithm and support vector machines

A New Method for Revealing Traffic Patterns in Video Surveillance using a Topic Model

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