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TECHNIQUE FOR IDENT;Critical Review on Practical S;RECOGNITION OF TAMIL SYLLABLES;UNDERSTANDING USER SEARCH BEHA;Power Management using WSN-Bas;SINGLE FRAME SUPER RESOLUTION ;SEGMENTATION AND QUALITY ANALY;EFFICIENTLY MINING CLOSED SEQU;REAL-TIME OBJECT DETECTION IN ;Personnel Recommendation Syste;LOW-POWER WIRELESS ECG ACQUISI;A NOVEL AUTHENTICATION SYSTEM ;Petrol pump automation using R;E-MDDR SCHEDULING ALGORITHM FO;CSR initiated with an agog or ;A NEW STEP IN BRAIN COMPUTER I;Multiple Target Tracking using;Comparative study of Software ;AN IMPLEMENTATION OF EIS-SVM C;Low Area and Low Power Perform;PROTECTING ROUTE ANONYMITY IN ;IMPLEMENTING CIPHER TEXT POLIC;Enhanced life time of Wireless;ANALYSIS EFFECIENY OF GRAPH C;SEGMENTATION AND QUALITY ANALY;UNCONVENTIONAL AND OPTIMIZED M;Speech Recognition of Tamil Ph;SOCIO PSYCHO ECONOMICS KNOW;Student Prediction System Usin;Segmentation and Classificatio;Personality trait- converging ;Comparitive Analysis of Optimi;hyperspectral image 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MULTISPEC;A SEMANTIC BASED ONTOLOGY MAPP;ENDOCARDIUM SEGMENTATION: AN A;AN ADJUSTABLE SPEED CONTROL OF;A study on Post Merger and Acq;Load Balancing and Scheduling ;Adaptive Light Control and Veh;EFFICIENT AND SECURE DATA HID;To Measure the Performance wit;A Study of Clustering Based Al;Orientation Field Reconstructi;Green Growth Initiatives --- A;PRESERVING THE GROWTH OF CROPS;CORTICAL SURFACE RECONSTRUCTIO;SOME LANGUAGES UNDER THE SUPER;Graph Community Detection_Norm;SATELLITE IMAGE PROCESSING FOR;DETECTION AND PREVENTION OF UN;Indexing and Query Processing ;A Review for Cluster Based Rou;Sentiment Analysis in Malayala;TOP-K SEARCH ON GRAPHS WITH M;Survey of Association Rule Min;Throughput erasure channel;Testbed Implementation of Spec;Mobile Data Gathering With Min;information technology;Leaders and Entrepreneurs invi;RESOLUTION ENRICHMENT USING GP;FRUIT FLY K-MEANS CLUSTERING A;ENERGY EFFICIENT ROUTING IN CO;RELIABLE DYNAMIC SOURCE ROUTIN;A SURVEY ON MULTICAST ROUTING ;SECUProposed student prediction system is most vital approach which may be used to differentiate the student data/information on the basis of the student performance. Managing placement and training records in any larger organization is quite difficult as the student number are high; in such condition differentiation and classification on different categories becomes tedious. Proposed fuzzy inference system will classify the student data with ease and will be helpful to many educational organizations. There are lots of classification algorithms and statistical base technique which may be taken as good assets for classify the student data set in the education field. In this paper, Fuzzy Inference system has been applied to predict student performance which will help to identify performance of the students and also provides an opportunity to improve to performance. For instance, here we will classify the student’s data set for placement and non-placement classes.