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Obtaining Crisp Priorities for Triangular and Trapezoidal Fuzzy Judgments

Computer Systems Science & Engineering 2022年第4期41卷 157-170页

作者： raman Kumar goyal Jaskirat Singh Nidhi Kalra Anshu Parashar Gagan Singla Sakshi Kaushal Computer Science and Engineering Department Thapar Institute of Engineering and TechnologyPatialaPunjabIndia Computer Science and Engineering University Institute of Engineering and TechnologyPanjab UniversityChandigarhIndia

This paper proposes anoptimal fuzzy-based model for obtaining crisp priorities for Fuzzy-AHP comparison *** judgments cannot be given for real-life situations,as most of these include some level of fuzziness and *** these situations,judgments are represented by the set of fuzzy *** of the fuzzy optimization models derive crisp priorities for judgments repre-sented with Triangular Fuzzy Numbers(TFNs)*** do not work for other types of Triangular Shaped Fuzzy Numbers(TSFNs)and Trapezoidal Fuzzy Numbers(TrFNs).To overcome this problem,a sum of squared error(SSE)based optimization model is *** some other methods,the proposed model derives crisp weights from all of the above-mentioned fuzzy judgments.A fuzzy number is simulated using the Monte Carlo method.A threshold-based constraint is also applied to minimize the deviation from the initial *** Algorithm(GA)is used to solve the optimization *** have also conducted casestudiesto show the proposed approach’s advantages over the *** show that the proposed model outperforms other models to minimize SSE and deviation from initial ***,the proposed model can be applied in various real time scenarios as it can reduce the SSE value upto 29%compared to the existing studies.

关键词： Analytic hierarchy process comparison matrices priority vectors fuzzy judgments triangular fuzzy numbers triangular-shaped fuzzy numbers trapezoidal fuzzy numbers

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Driving Style Recognition System Using Smartphone Sensors Based on Fuzzy Logic

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Computers, Materials & Continua 2021年第11期69卷 1967-1978页

作者： Nidhi Kalra raman Kumar goyal Anshu Parashar Jaskirat Singh Gagan Singla Department of Computer Science and Engineering Thapar Institute of Engineering and TechnologyPatiala147001PunjabIndia Computer Science and Engineering University Institute of Engineering and TechnologyPanjab University160014ChandigarhIndia

Every 24 seconds,someone dies on the road due to road accidents and it is the 8th leading cause of death and the first among children aged 15–29 years.1.35 million people globally die every year due to road traffic *** additional 20–50 million suffer from non-fatal injuries,often resulting in longterm *** costs around 3%of Gross Domestic Product to most countries,and it is a considerable economic *** governments have taken various measures such as better road infrastructures and strict enforcement of motor-vehicle laws to reduce these ***,there is still no remarkable reduction in the number of *** ensure driver safety and achieve vision of zero accidents,there is a great need to monitor drivers’driving *** of the existing driving behavior monitoring solutions are based on expensive hardware *** most people are using smartphones in the modern era,a system based on mobile application is proposed,which can reduce the cost for developing intelligent transport systems(ITS)to a large *** this paper,we utilize the accelerometer sensor data and the global positioning system(GPS)sensor deployed in smartphones to recognize driving and speeding events.A driving style recognition system based on fuzzy logic is designed to classify different driving styles and control reckless driving by taking the longitudinal/lateral acceleration and speed as input ***,the proposed system uses fuzzy logic rather than taking the crisp values of the *** indicate that the proposed system can classify reckless driving based on fuzzy logic and,therefore,reduce the number of accidents.

关键词： Fuzzy logic accelerometer global positioning system driving style

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LOD Cloud Mining for Prognosis Model(Case Study: Native App for Drug Recommender System)

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Advances in Internet of Things 2014年第3期4卷 20-28页

作者： Nidhi Kushwaha raman goyal Pramiti Goel Sidharth Singla Om Prakash Vyas Department of Information Technology Indian Institute of Information Technology (IIIT-A) Allahabad India

The goal of this project is to use the Semantic Web Technologies and Data Mining for disease diagnosis to assist health care professionals regarding the possible medication and drug to prescribe (Drug recommendation) according to the features of the patient. Numerous Decision Support Systems (DSS) and Expert Systems allow medical collaboration, like in the differential diagnosis specific or general. But, a medical recommendation system using both Semantic Web technologies and Data mining has not yet been developed which initiated this work. However, it should be mentioned that there are several system references about medicine or active ingredient interactions, but their final goal is not the Drug recommendation which uses above technologies. With this project we try to provide an assistant to the doctor for better recommendations. The patient will also able to use this system for explanation of drugs, food interaction and side effects of corresponding drugs.

关键词： Linked Life Drug Data Cloud Recommender System Data Mining Semantic Web

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