World Journal of Engineering Research and Technology (WJERT) has indexed with various reputed international bodies like : Google Scholar , Index Copernicus , Indian Science Publications , SOCOLAR, China , International Institute of Organized Research (I2OR) , Cosmos Impact Factor , Research Bible, Fuchu, Tokyo. JAPAN , Scientific Indexing Services (SIS) , Jour Informatics (Under Process) , UDLedge Science Citation Index , International Impact Factor Services , International Scientific Indexing, UAE , International Society for Research Activity (ISRA) Journal Impact Factor (JIF) , International Innovative Journal Impact Factor (IIJIF) , Science Library Index, Dubai, United Arab Emirates , Scientific Journal Impact Factor (SJIF) , Science Library Index, Dubai, United Arab Emirates , Eurasian Scientific Journal Index (ESJI) , Global Impact Factor (0.342) , IFSIJ Measure of Journal Quality , Web of Science Group (Under Process) , Directory of Research Journals Indexing , Scholar Article Journal Index (SAJI) , International Scientific Indexing ( ISI ) , Scope Database , 

World Journal of Engineering
Research and Technology

( An ISO 9001:2015 Certified International Journal )

An International Peer Reviewed Journal for Engineering Research and Technology

ISSN 2454-695X

Impact Factor : 5.924

ICV : 79.45

News & Updation

  • Article Invited for Publication

    Article are invited for publication in WJERT Coming Issue

  • ICV

    WJERT Rank with Index Copernicus Value 79.45 due to high reputation at International Level


    FEBRUARY 2023 Issue has been successfully launched on 1 February 2023.

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    Its Our pleasure to inform you that, WJERT February 2023 Issue has been Published, Kindly check it on

  • WJERT New Impact Factor

    Its our Pleasure to Inform you that WJERT Impact Factor has been increased from  5.549 to 5.924 due to high quality Publication at International Level




*Saloni Kumari and Pawan Kumar


Stock market is one among them which needs the prediction future market to invest in the new enterprise or to sell their existing shares to get profit. This need the efficient prediction technique which studies the previous exchanges of stock market and gives the future prediction based on that. This article proposed the prediction system of stock market price based on the exchange takes place in previous scenario. The system studies the diverging effect of market price of product in a particular time gap and analyse its future trend whether it’s loss or gain. During the system of thinking about diverse strategies and variables that should be taken into account, we observed out that strategies like random forest, Support vector machine and regression algorithm. Support vector regression is a beneficial and effective gadget gaining knowledge of approach to apprehend sample of time collection dataset. The data collected for the four years duration which was accumulated to get the expecting prices of the share of the firm. It can produce true prediction end result if the fee of essential parameters may be decided properly. It has been located that the guide vector regression version with RBF kernel indicates higher overall performance while in comparison with different models.

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