International Journal of Engineering Science Technologies最新文献

{"title":"STOCK PRICE PREDICTION USING SUPPORT VECTOR REGRESSION AND K-NEAREST NEIGHBORS: A COMPARISON","authors":"Madhumita Ghosh, Ravi Gor","doi":"10.29121/ijoest.v6.i4.2022.354","DOIUrl":"https://doi.org/10.29121/ijoest.v6.i4.2022.354","url":null,"abstract":"Supervised Learning is an important type of Machine learning. It includes regression and classification problems. In Supervised learning, Support Vector Machine (SVM) and K-Nearest Neighbors (KNN) can be used for classification and regression. Here, both algorithms are used for regression problem. The stock data is trained by SVR and KNN respectively to predict the stock price of the next day using python tool. Both algorithms are compared and it is observed that the price predicted by SVR is closer as compared to KNN.","PeriodicalId":331301,"journal":{"name":"International Journal of Engineering Science Technologies","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124828013","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":"BITCOIN PRICE PREDICTION WITH COVID-19 SENTIMENT USING LSTM NEURAL NETWORK","authors":"Shachi Bhavsar, Ravi Gor","doi":"10.29121/ijoest.v6.i4.2022.355","DOIUrl":"https://doi.org/10.29121/ijoest.v6.i4.2022.355","url":null,"abstract":"Cryptocurrencies are nowadays getting popular for investment due to its various benefits such as low transaction cost, blockchain secured platform, profit, etc. Bitcoin being top of the market capitalization currency, gained more popularity during covid-19 pandemic. This study focuses on bitcoin price prediction with covid-19 sentiment. Here Long Short Term Memory Deep learning model based on machine learning is used for price prediction. At the end both results i.e., with covid-19 sentiment and without it are compared which shows model performs better by adding sentiments.","PeriodicalId":331301,"journal":{"name":"International Journal of Engineering Science Technologies","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129333971","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":"STOCK PRICE PREDICTION USING GRID HYPER PARAMETER TUNING IN GATED RECURRENT UNIT","authors":"Shachi Bhavsar, Ravi Gor","doi":"10.29121/ijoest.v6.i3.2022.345","DOIUrl":"https://doi.org/10.29121/ijoest.v6.i3.2022.345","url":null,"abstract":"Nowadays people are using social media to show their talent, to voice their viewpoint to society, etc. The use of social media has drastically grown during and after pandemic. Since, the power of social media is known to us, it would be beneficial to invest in such trending companies. But, understanding market pattern will be required to get maximum benefit from stock market, otherwise it may lead to losses. Machine learning is an essential tool for predicting such tasks. Here deep learning based Gated Recurrent Unit neural network is used for prediction. To develop optimized model, grid search algorithm is used for Gated Recurrent Unit hyper parameter tuning. Also, the hyper parameter values obtained by the model was used to verify and predict stock prices for other companies.","PeriodicalId":331301,"journal":{"name":"International Journal of Engineering Science Technologies","volume":"287 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132268885","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":"HEALTH INSURANCE PREMIUM PREDICTION USING BLOCKCHAIN TECHNOLOGY AND RANDOM FOREST REGRESSION ALGORITHM","authors":"Madhumita Ghosh, Ravi Gor","doi":"10.29121/ijoest.v6.i3.2022.346","DOIUrl":"https://doi.org/10.29121/ijoest.v6.i3.2022.346","url":null,"abstract":"Blockchain technology is based on a sequence of blocks, where each block carries a certain amount of information. Medical records can be cryptographically secured in the health insurance ecosystem with blockchain technology. Here, blockchain technology model is used to create a user interface for storing data block wise. Also, Insurance premium is predicted using Support Vector Regression, Lasso Regression, Ridge Regression, Multiple Linear Regression and Random Forest Regression algorithms. Out of all these algorithms, Multiple Linear Regression algorithm gives the better result.","PeriodicalId":331301,"journal":{"name":"International Journal of Engineering Science Technologies","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128861378","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":"THE EFFECTS OF BUILDING INFORMATION MODELING (BIM) IMPLEMENTATION IN THE SUCCESS OF CONSTRUCTION PROJECTS","authors":"Herumanta Bambang, Rizky Citra Islami, A. U. Hazhiyah","doi":"10.29121/ijoest.v6.i3.2022.326","DOIUrl":"https://doi.org/10.29121/ijoest.v6.i3.2022.326","url":null,"abstract":"Building Information Modeling (BIM) is one of the most exciting recent advances in the field of architecture, enginering and construction (AEC), which is a significant advance in digital technology for virtual building modeling. The aim of this final project is to evaluate the impact of the benefits of BIM adoption, BIM adoption factors, challanges and barriers, both partially and simultaneously on critical success factors in Building Information Modeling (BIM) based projects. Respondents of this study were 40 contractors and construction consultants representing 14 construction companies in Indonesia with experience using Building Information Modeling (BIM) based applications. The method used is in the form of quantitative research using descriptive and statistical analysis through the SPSS 25.0 application. The results of the analysis showed that: (a) the advantages of adopting BIM have a positive and significant effect on critical success factors, (b) factors related to BIM adoption have a positive and significant effect on critical success factors (c) challenges and obstacles do not have a negative effect on critical success factor, (d) simultaneously there is an effect of the advantages of adopting BIM, factors related to BIM adoption, challenges and obstacles to critical success factors in Building Information Modeling (BIM) based projects.\u0000 ","PeriodicalId":331301,"journal":{"name":"International Journal of Engineering Science Technologies","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123792265","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":"THE SILTING UP OF VEGETABLE CROP AREA IN GANDIOLAIS (NORTHERN COAST OF SENEGAL)","authors":"D. F., Tine A. K., Biaye L","doi":"10.29121/ijoest.v6.i3.2022.246","DOIUrl":"https://doi.org/10.29121/ijoest.v6.i3.2022.246","url":null,"abstract":"The Gandiolais is part of the large \"Niayes\" ecosystem in the Saint Louis region. It is bordered by active dunes from the recent Quaternary delimiting interdune depressions in which the sub-surface water table has favored the practice of vegetable crops. These vegetable cropping areas are production systems that are now facing silting up. \u0000Our results show that this silting is due to deflation and/or mass movement of dune soils. These two phenomena are generated by the sensitivity of dune soils to deflation by trade winds and drought. The resulting negative consequences include, among others, the abandonment of vegetable cropping activities by farmers. \u0000Solutions to reduce trade wind speeds and improve the cohesion and structuring of dune soils are proposed. In particular, we recommend the creation of windbreaks and the reconstitution of sufficient plant cover.","PeriodicalId":331301,"journal":{"name":"International Journal of Engineering Science Technologies","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114947458","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":"SOLVING MULTICAST ROUTING PROBLEM USING PARTICLE SWARM OPTIMIZATION","authors":"S. Behera, Prasanta Kumar Raut","doi":"10.29121/ijoest.v6.i3.2022.330","DOIUrl":"https://doi.org/10.29121/ijoest.v6.i3.2022.330","url":null,"abstract":"In a given network there exist many paths from source to destination, among all selected paths finding the optimal shortest path is a challenging task. In this research paper, we proposed a new concept of particle swarm optimization technique, called swarm intelligence, to solve the multicast routing problem to find out the optimal route associated with a network, here we also used triangular fuzzy number tools to encode particles in PSO (particle swarm optimization), first it breaks the network into small spaces and from the small space it computes the optimal path.","PeriodicalId":331301,"journal":{"name":"International Journal of Engineering Science Technologies","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121922963","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":"STABILITY-INDICATING HPLC METHOD FOR THE DETERMINATION OF RELATED SUBSTANCES IN LANSOPRAZOLE INTERMEDIATE","authors":"Balaji Nagarajan, G. Manoharan","doi":"10.29121/ijoest.v6.i3.2022.329","DOIUrl":"https://doi.org/10.29121/ijoest.v6.i3.2022.329","url":null,"abstract":"A novel, reversed-phase liquid chromatographic method was developed and validated for the determination of related substances in lansoprazole intermediate. Symmetric peak shape was on a C18 stationary phase with the dimensions of 250 mm column length, 4.6 mm as internal diameter, 5 microns particles with an economical and straightforward mass-compatible mobile phase combination of formic acid/triethylamine and acetonitrile delivered in gradient mode at a flow rate of 1.0 mL/min at 260 nm. The resolution between lansoprazole intermediate (LAN20) and its impurities (LAN20-I & LAN20-II) in the developed method was more than 2.0, indicating a significant separation. Regression analysis shows a correlation coefficient greater than 0.999 for lansoprazole intermediate and its related substances. The detection and quantitation limits of lansoprazole intermediate and its impurities are 0.01% and 0.005%. This method indicates that the recovery at different levels is 90 to 110% accurate. The test solution was stable in the diluent for 48 h and subjected to stress conditions. The mass balance was close to 99.5%.","PeriodicalId":331301,"journal":{"name":"International Journal of Engineering Science Technologies","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131124448","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":"WASTE-TO-ENERGY: A PROMISING MARITIME TRANSPORT TECHNOLOGY","authors":"Thangalakshmi s. Dr., Sivasami K.","doi":"10.29121/ijoest.v6.i3.2022.327","DOIUrl":"https://doi.org/10.29121/ijoest.v6.i3.2022.327","url":null,"abstract":"Everything in the world, including the shipping industry, is powered by energy. There are numerous advanced energy-generation strategies, but it would be greatly valued if energy could be consistently derived from ship waste. Waste disposal is a difficult task in the shipping industry, so many studies are being conducted to find better ways to dispose of waste. According to regulatory agencies, India has a large source of both industrial and urban organic waste. The shipping industry, like any other, necessitates massive amounts of energy. On a daily basis, a massive amount of waste is generated, ranging from small crafts to ultra-large vessels (aerobic as well as anaerobic). So, there is a significant opportunity for capturing the energy from these waste, and both the difficulty of waste disposal and the depletion of conventional energy sources can be effectively addressed concurrently. This paper examines various means of generating energy from waste. Furthermore, the current state of Waste-to-Energy (WTE) in our country and around the world is discussed.\u0000Motivation/Background: There is a perennial need for energy in all industry. This energy is pivotal in marine sector. There is huge amount of waste disposal into sea and IMO is keen on pollution control and de-carbonization. So, converting the waste serves two purposes viz. pollution control and green energy generation.\u0000Method: Various techniques for generating energy from waste had been discussed.\u0000Results: Waste-To-Energy is still a relatively unexplored technology in the shipping industry. Large cruise ships generate massive quantities of waste. This in and of itself represents a large avenue for WTE as a source of renewable energy on board ships. There are very few manufacturers venturing into the WTE segment to create power from ship waste. Scanship, a Norwegian ship waste management system manufacturer, has established a system that uses microwave-assisted pyrolysis to transform carbon-based waste generated on ships into biofuels.\u0000Conclusions: WTE is also a relatively new concept in the shipping industry. Countries such as Norway, which is successfully operating WTE plants on land, are progressively migrating the technology and paving the way for others. More initiatives like these can radically decrease the amount of waste that ships discharge into the sea, resulting in a more comprehensive ecosystem for all life forms.","PeriodicalId":331301,"journal":{"name":"International Journal of Engineering Science Technologies","volume":"63 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120990837","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":"IDENTIFICATION AND CODING OF ELLIOT WAVE PATTERN","authors":"Vaidehi Vaghela, Ravi Gor","doi":"10.29121/ijoest.v6.i3.2022.325","DOIUrl":"https://doi.org/10.29121/ijoest.v6.i3.2022.325","url":null,"abstract":"Prediction of stock price and modelling of market pattern are quite difficult and complex to understand itself. There are hidden factors of market like effect of news, sentiment of crowd etc. which play an important role of modelling the market pattern. The modelling of market patterns was primarily developed by R.N. Elliott. The Elliott Wave theory was described subjectively in literature and wave patterns cannot be identify easily. In this work, we mainly focus on identification of wave pattern through Fractal indicators and Awesome Oscillator using R programming.","PeriodicalId":331301,"journal":{"name":"International Journal of Engineering Science Technologies","volume":"233 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131512714","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}