Samvakti Journal of Research in Information Technology最新文献

{"title":"An analysis of Artificial Intelligence and its role in the cryptocurrency","authors":"Shikha Singh","doi":"10.46402/2023.02.30","DOIUrl":"https://doi.org/10.46402/2023.02.30","url":null,"abstract":"","PeriodicalId":296679,"journal":{"name":"Samvakti Journal of Research in Information Technology","volume":"21 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130802388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A NOVEL METHOD TO ANALYZE RISK AND PERFORMANCE ANALYSIS FOR MUTUAL FUNDS","authors":"P. Das, Siddharth Nanda","doi":"10.46402/202007.50.278","DOIUrl":"https://doi.org/10.46402/202007.50.278","url":null,"abstract":"Mutual Funds investments have attracted attention and interest in the recent times as it is considered to be safe and has provided investors with less risk at returns. The Indian market, in a similar manner, has witnessed the diversified growth of mutual funds throughout many years. From 2016 onwards, the Indian market is thronged with more than 2,500 mutual fund plans, and each plan is expected to bring higher returns than its peers. For ordinary investors, this is a challenge to choose the best investment portfolio, so it is essential to analyze the performance of these funds. In understanding and analyzing the historical performance of mutual funds, it does not assure future performance, but this may give some insight into the performance of the fund under different market conditions. In this research work, we analyzed the data and solved several research problems with the use of R Studio tool. These include measuring the performance of specific plans based on risks and returns, and compare the performance of these selected plans with the benchmark index to see if the plan's performance is better than the benchmark. We also introspect which parameters affect the schemes in a particular way based on performance and propose strategies for investing in mutual funds. Therefore, our findings are of great relevance to the investment public.","PeriodicalId":296679,"journal":{"name":"Samvakti Journal of Research in Information Technology","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129557822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An analysis of economy plunge during a pandemic and assumed reactivation policies","authors":"Yash Khare, Siddharth Nanda","doi":"10.46402/202007.50.273","DOIUrl":"https://doi.org/10.46402/202007.50.273","url":null,"abstract":"Corona virus outbreak has put the world on hold and this has got the economies down to alarming levels. And this is the time when policies should be framed according to the downfall trends to re-strengthen the economy. Corona virus has swiftly transformed from a health care danger to a financial crisis. In this paper, first we see how the number of cases are rising and how the world’s GDP is falling down with respect to time. In this paper we have predicted the Public debt to GDP Ratio of India in 2021 using Machine Learning algorithm. This paper also shows the trends in the unemployment rate in India and a heat map of cases around the world. This paper also presents some policies to improve the current financial situation. The 5 policies include: Economic framework, Public health policy framework, Gradual opening of the lockdown, Educational Transformations, and the Public private partnership.","PeriodicalId":296679,"journal":{"name":"Samvakti Journal of Research in Information Technology","volume":"65 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120899406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AN INNOVATIVE TIME SERIES BASED METHOD OF FORECASTING MONTHLY SALES OF CHAMPAGNE","authors":"Aseen Saxena, Siddharth Nanda","doi":"10.46402/202007.50.281","DOIUrl":"https://doi.org/10.46402/202007.50.281","url":null,"abstract":"Time series analysis is a process which deals with data to identify trends and forecast future happening. The data used in this analysis is known time series data which is in a time interval format. The data was used is based on the data which is taken in a different interval of time, known as time-series data. Balancing of demand and supply is based on the accurate prediction of sales in future, if there is a lack of efficient forecasting than it can a challenge to run the business and make a good profit. Time-series forecasting is one of the most commonly used approaches in day-to-day in many organizations. Marketing research also uses time-series data to find their future predictions. Its main strength is to study the change of various event in time so that it can be a strong tool for marketers. Approaches of time series analysis are autoregressive integrated moving average(ARIMA), seasonal autoregressive integrated moving average(SARIMA), autoregressive moving average(ARMA), moving average(MA) and autoregression(AR). This paper consists of predicting the monthly sales of champagne by using time series and will also predict the future monthly sales of champagne. ARIMA and SARIMAX model was used for forecasting and predicted the sales of champagne for 10 years. Champagne dataset was used in this research and using time series, predicting model was prepared. It is predicting good and giving good results. Keyword: time series analysis, forecasting, sales prediction, future prediction An innovative time series based method of forecasting monthly sales of champagne Page No. 78 INTRODUCTION The main purpose of this paper is to find the future forecasting of the monthly sales of champagne. ARIMA and SARIMA model were used to make a model and which would be useful to predict the monthly sales of French champagne. We will find a plot which shows the prediction for The monthly sales of the champagne dataset is a time series dataset, which can be used to find the future prediction based on the past data points of the dataset. The dataset consists of months and total sales from 01/1964 to 09/1972. There are 104 entries, and the sales are counted in millions[8]. Forecasting is the process of determining the future happening. Forecasting can be used in many fields such as what is the GDP rate after five years, profits or loss after one year, decrease or increase in shares of a company, demand of a product after six months, climate forecasting. Forecasting is required to run an organization, so if there is an unfortunate happening in the future so it can be handled easily. The data which is recorded based on time is called time-series data. Examples are the annual income of an organization, the demand for a product, day-to-day temperature, and the number of passengers travelling. The data which is calculated per second, per minute, hourly, daily, weekly, monthly, yearly are all comes under time-series data. It can be used to do better planning and can sugges","PeriodicalId":296679,"journal":{"name":"Samvakti Journal of Research in Information Technology","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125767934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A STUDY AND SURVEY ON CONTENT-BASED IMAGE RETRIEVAL USING LOW LEVEL FEATURES FOR MOBILE DEVICES","authors":"M. Y. Patil, Dr.Amol B. Kasture","doi":"10.46402/202007.343.48.255","DOIUrl":"https://doi.org/10.46402/202007.343.48.255","url":null,"abstract":"In the arena of Image Processing, Image Retrieval has developed one of the greatest dynamic research parts in the previous few years. The image retrieval is interesting and fastest developing methodology in all the fields. It is effective and well-organized approach for retrieving the image from large image scale database. Content based Image retrieval (CBIR) means search the contents of the image rather than the information and capture images from database as per the user’s requirement. In Content based Image Retrieval (CBIR), images are retrieved by their visual content such as color, texture and shapes. It is a technique to take input as query object and gives output from an image database. Mobile image retrieval is one of the most exciting and fastest growing research fields in the area of multimedia technology. Modern multimedia mobile devices are prepared with camera and higher storage abilities; this desires the need of effective multimedia content management concluded in several networks. In this paper surveys have been conducted on some CBIR features such as color, texture and shape retrieval of images from the large-scale image database and also study to compare content-based image retrieval features like color, texture and shape for efficient and accurate image retrieval on mobile devices. After going through comprehensive analysis of CBIR techniques so this paper gives A study and survey on content-based image retrieval using low level features for mobile devices. Page No. 42 summarization of the different features like color, texture and shape of images with their functionality for content-based image retrieval systems (CBIR).","PeriodicalId":296679,"journal":{"name":"Samvakti Journal of Research in Information Technology","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132988628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Novel Financial Analysis of Stock Market","authors":"Anjali Shukla, Siddharth Nanda","doi":"10.46402/202007.50.284","DOIUrl":"https://doi.org/10.46402/202007.50.284","url":null,"abstract":"The financial Analysis of stock market exchange prediction is the confirmation of participating to decide the future association of a group stock or other currency product exchange on a money related business. The effective expectation of a stock's future cost will expand speculator's benefits. This paper proposes a machine learning model to foresee financial exchange cost. The proposed calculation incorporates Particle Swarm Advancement and least square help vector machine. Particle Swarm Advancement calculation chooses best boundaries for vector machine to maintain a strategy based distance from over-fitting and neighbour minima issues and improve expectation exact result. The access of proposed approach was applied and utilizing thirteen benchmark financials datasets and copied neural system with LevenbergMarquardt theory. The outcomes indicated that the proposed model has better forecast exactness and the capability of PSO calculation in upgrading vector machine. The principle target of writing this paper is to show the location of the best model to expect the estimation of the stock exchange. Continuing the way towards consideration of various rules and algorithms which must be included, we research on the methods like improper woodland, vector machine which were not in wrong used completely. I am going to represent and a kind of survey which is a successfully achievable algorithm to previse the stock market development strategy with a high accuracy. The main objective we have considered is the data of the financial exchange costs from earlier year.","PeriodicalId":296679,"journal":{"name":"Samvakti Journal of Research in Information Technology","volume":"34 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113973441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}