{"_id":"mQ389Kx5WPjMCQuag","bibbaseid":"usha-resourcemanagementandsimulationtoolsinfogcomputingacomparativestudy-2020","author_short":["Usha, V."],"bibdata":{"bibtype":"article","type":"article","title":"Resource Management and Simulation Tools in Fog Computing – A comparative Study","volume":"9","issn":"22783091","doi":"10.30534/ijatcse/2020/125912020","abstract":"The paper presents the possibility of application of fuzzy logic to determine the odour intensity of model, ternary gas mixtures (α-pinene, toluene and triethylamine) using electronic nose prototype. The results obtained using fuzzy logic algorithms were compared with the values obtained using multiple linear regression (MLR) model and sensory analysis. As the results of the studies, it was found the electronic nose prototype along with the fuzzy logic pattern recognition system can be successfully used to estimate the odour intensity of tested gas mixtures. The correctness of the results obtained using fuzzy logic was equal to 68%.","number":"1","journal":"International Journal of Advanced Trends in Computer Science and Engineering","author":[{"propositions":[],"lastnames":["Usha"],"firstnames":["Vadde"],"suffixes":[]}],"month":"February","year":"2020","keywords":"context, context life, context-awareness, cycle, internet of things, iot, self-learning","pages":"875–882","bibtex":"@article{Devi2015b,\n\ttitle = {Resource {Management} and {Simulation} {Tools} in {Fog} {Computing} – {A} comparative {Study}},\n\tvolume = {9},\n\tissn = {22783091},\n\tdoi = {10.30534/ijatcse/2020/125912020},\n\tabstract = {The paper presents the possibility of application of fuzzy logic to determine the odour intensity of model, ternary gas mixtures (α-pinene, toluene and triethylamine) using electronic nose prototype. The results obtained using fuzzy logic algorithms were compared with the values obtained using multiple linear regression (MLR) model and sensory analysis. As the results of the studies, it was found the electronic nose prototype along with the fuzzy logic pattern recognition system can be successfully used to estimate the odour intensity of tested gas mixtures. The correctness of the results obtained using fuzzy logic was equal to 68\\%.},\n\tnumber = {1},\n\tjournal = {International Journal of Advanced Trends in Computer Science and Engineering},\n\tauthor = {Usha, Vadde},\n\tmonth = feb,\n\tyear = {2020},\n\tkeywords = {context, context life, context-awareness, cycle, internet of things, iot, self-learning},\n\tpages = {875--882},\n}\n\n\n\n","author_short":["Usha, V."],"key":"Devi2015b","id":"Devi2015b","bibbaseid":"usha-resourcemanagementandsimulationtoolsinfogcomputingacomparativestudy-2020","role":"author","urls":{},"keyword":["context","context life","context-awareness","cycle","internet of things","iot","self-learning"],"metadata":{"authorlinks":{}},"downloads":0,"html":""},"bibtype":"article","biburl":"https://bibbase.org/zotero/wmarshedi","dataSources":["6oX56jrCWfxNpSJQs"],"keywords":["context","context life","context-awareness","cycle","internet of things","iot","self-learning"],"search_terms":["resource","management","simulation","tools","fog","computing","comparative","study","usha"],"title":"Resource Management and Simulation Tools in Fog Computing – A comparative Study","year":2020}