Optimization of a pump health monitoring system using fuzzy logic

Kleinmann, Stefan; Stetter, Ralf; Prasad, Praveen Kumar Kubendra

doi:10.1109/systol.2013.6693815

Cited by 2 publications

(2 citation statements)

References 4 publications

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“…In general, a statistics may be represented as a sequence (x1, x2, x3 ..., xn) containing n information points xi. These information points will comprises real numbers, for instance of the river level or the voltage of an EEG derivation [8] measured at sure usually equal points in time; or additional advanced, they'll be extremely three-dimensional, e.g. the time of the transaction, a customer ID and bought items.…”

Section: Time Series Forecastingmentioning

confidence: 99%

Fuzzy Logic Classification Approach for Prediction of Patient Data in Health Care System using Data Mining Analysis

Kaur¹,

Goyal²

2018

IJMTT

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Data Mining is the process of extracting data from huge information sets through various techniques drawn from the sector of Statistics, Machine Learning and information base Management Systems. Data processing, popularly known as data discovery in huge information, is carrying out of operations on data to retrieve, transform, or classify information. Authors propose a study of third-dimensional information deposit and mining approach to deal with the problems of organizing, reportage and documenting polygenic disease cases as well as causalities. Data processing procedures views representational process similarity and comparison of attributes extracted from the information gathered. Statistic statement takes the past values of a statistic and uses them to forecast the longer term values. Fuzzy regression strategies have been used to develop preferences models that correlate the engineering characteristics with shopper preferences relating to a replacement product; the patron preference models offer a platform, wherever by product developers will decide the engineering characteristics so as to satisfy shopper preferences before developing the merchandise. Recent analysis shows that these fuzzy regression strategies area units are normally used to model client preferences. We tend to propose a Testing the strength of Exponential Regression Model over regression Model to predict the patient data.

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Section: Time Series Forecastingmentioning

confidence: 99%

Fuzzy Logic Classification Approach for Prediction of Patient Data in Health Care System using Data Mining Analysis

Kaur¹,

Goyal²

2018

IJMTT

View full text Add to dashboard Cite

show abstract

“…In general, a statistic s may be represented as a sequence (x1, x2, x3 ..., xn) containing n information points xi. These information points will comprises real numbers, for instance of the river level or the voltage of an EEG derivation [8] measured at sure usually equal points in time; or additional advanced, they'll be extremely three-dimensional, e.g. the time of the transaction, a customer ID and bought items.…”

Section: -Fuzzy Based Regression Analysismentioning

confidence: 99%

Regression Based Fuzzy Logic Classification Approach for Non Linear Data Set in Health Care System

Jit¹,

Gill²,

Pandey³

et al. 2016

Fourth International Conference on Advances in Computing, Communication and Information Technology CCIT- 2016

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Data processing, popularly known as data discovery in giant information, allows companies and organizations to form calculated choices by grouping, accumulating, analyzing and accessing company information. Authors propose a sturdy metaphysics based mostly thirddimensional information deposit and mining approach to deal with the problems of organizing, reportage and documenting polygenic disease cases as well as causalities. data processing procedures, during which map and information views representational process similarity and comparison of attributes extracted from warehouses, square measure utilized in this studies, for understanding the ailments supported gender, age, geography, food habits and hereditary traits. Statistic statement takes the past values of a statistic and uses them to forecast the longer term values. Fuzzy regression strategies have normally been wont to develop shopper preferences models that correlate the engineering characteristics with shopper preferences relating to a replacement product; the patron preference models offer a platform, wherever by product developers will decide the engineering characteristics so as to satisfy shopper preferences before developing the merchandise. Recent analysis shows that these fuzzy regression strategies area units normally won"t to model client preferences. We tend to propose a Testing the strength of Exponential Regression Model over regression toward the mean Model.

show abstract

Optimization of a pump health monitoring system using fuzzy logic

Cited by 2 publications

References 4 publications

Fuzzy Logic Classification Approach for Prediction of Patient Data in Health Care System using Data Mining Analysis

Fuzzy Logic Classification Approach for Prediction of Patient Data in Health Care System using Data Mining Analysis

Regression Based Fuzzy Logic Classification Approach for Non Linear Data Set in Health Care System

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