Indian Journal Of Science And Technology最新文献

{"title":"Impact of Behavioral Biases on Investors’ Stock Trading Decisions: A Comprehensive Quantitative Analysis","authors":"Anurag Shukla, Manish Dadhich, Dipesh Vaya, Anuj Goel","doi":"10.17485/ijst/v17i8.2845","DOIUrl":"https://doi.org/10.17485/ijst/v17i8.2845","url":null,"abstract":"Objective: This paper aims to investigate the impact of specified behavioral biases on investors' stock trading decisions in North India. It has been observed that most of the research works are based on financial theories, which affect investment decisions. But besides the theories nowadays, behavioral biases also play an important role in investment decisions, which was less focused in the previous literature. Methods: The study used primary data collected from a sample from North Indian States (Uttar Pradesh, Delhi, Haryana, and Punjab) through a structured questionnaire to analyze the impact of specified behavioral biases on investors' stock trading decisions. We used structural equation modelling to find out the significant impact of behavioral biases on stock trading and investment decisions. Findings: The investigation determined that the majority of the designated cognitive biases, such as the Overconfidence Bias, the Representativeness Bias, and the Herding Bias, exert a significant influence on the decisions about stock trading and investment made by investors. Novelty: The ample research in this domain has primarily occurred in various countries, with only a limited number of studies conducted specifically at the Indian level. Nevertheless, based on the literature review, it is evident that this study is groundbreaking in North India. The objective of this research is to enhance the effectiveness of financial advisors by gaining a deeper understanding of the psychological aspects of clients. This, in turn, will aid in developing portfolios tailored to individual behavior, aligning with client preferences. Recognizing and addressing behavioral biases is crucial for individual investors as they strive to make informed and successful financial decisions. Keywords: Behavioral Biases, Overconfidence (OC) bias, Representativeness Bias (RB), Herding Bias (HB), Structural Equation Modelling","PeriodicalId":508200,"journal":{"name":"Indian Journal Of Science And Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140455918","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":"Frequency and Spatial Domain-Based Approaches for Recognition of Indian Sign Language Gestures","authors":"B. V. Poornima, S. Srinath","doi":"10.17485/ijst/v17i7.2836","DOIUrl":"https://doi.org/10.17485/ijst/v17i7.2836","url":null,"abstract":"Objectives: The objective of this paper is to introduce and demonstrate an innovative approach for the recognition of Indian sign language gestures, with a focus on bridging communication gap between the deaf and hearing communities. The goal is to contribute to the development of effective tools and technologies that facilitate seamless communication between individuals using sign language and the people with no knowledge about sign language. Methods: The methodology consists of three key steps. First, data pre-processing involves resizing and contours extraction. Next, feature extraction employs Fourier descriptors for frequency domain analysis and gray-level-co-occurrence matrix for spatial domain analysis. Finally, various machine learning models including SVM, Random Forest, Logistic Regression, K-Nearest Neighbor and Naive Bayes are trained on a standard dataset. Findings: In our controlled experimental setup, we applied a diverse set of machine learning classifiers to evaluate the proposed approach for gesture recognition. Among the classifiers tested, K-Nearest Neighbors demonstrated the highest accuracy, achieving 99.82%. To validate the robustness of our approach, we employed k-fold cross-validation with 5 folds. Novelty: This study presents an innovative method for sign language recognition by employing a dual-domain fusion strategy that prominently emphasizes the frequency domain. Through the integration of Fourier descriptors, the research conducts a detailed frequency domain analysis to characterize the contour shapes of sign language gestures. The synergy with gray-level co-occurrence matrix texture features in the spatial domain analysis, contributes to the creation of a comprehensive feature vector. The proposed approach ensures a thorough exploration of gesture features, there by advancing the precision and efficacy of sign language recognition. Keywords: Indian Sign Language (ISL), Sign Language Recognition (SLR), Frequency domain, Spatial domain, Fourier descriptors, Gray level co­occurrence matrix (GLCM), K­ Fold","PeriodicalId":508200,"journal":{"name":"Indian Journal Of Science And Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139774178","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":"Machine Learning-based Inverse Design Model of a Transistor","authors":"Abhilipsa Sahoo, Kaushika Patel","doi":"10.17485/ijst/v17i7.3076","DOIUrl":"https://doi.org/10.17485/ijst/v17i7.3076","url":null,"abstract":"Objectives: To develop an inverse design model for transistors, utilizing machine learning algorithms to predict key design parameters specifically, the length and width based on specified gain and bandwidth requirements. And to conduct a comprehensive comparative analysis with existing literature, evaluating the efficacy and novelty of the proposed model in the context of semiconductor engineering challenges and methodologies. Methods: The comprehensive dataset, comprising 30,000 values generated through LTspice simulations, forms the basis for training the machine learning model. Utilizing a Random Forest regressor as the base model and a multi-output regressor as the main model, the project involves extensive data analysis, model development, and iterative fine-tuning. Findings: The outcomes demonstrate the efficacy of the developed model in accurately predicting transistor dimensions. Performance metrics, including Mean Absolute Error (MAE), Mean Squared Error (MSE), and R-squared, highlight the precision of the model in fulfilling the specified objectives. Novelty: This study introduces a novel approach to semiconductor device design optimization, showcasing the potential of machine learning to streamline the inverse design process. The use of a multi-output regressor, feature engineering, and fine-tuning through log transformation contribute to the innovative nature of the developed model. Keywords: Machine Learning (ML) model, Random Forest regressor, multi­output regressor, Feature engineering, Fine­tuning","PeriodicalId":508200,"journal":{"name":"Indian Journal Of Science And Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139775259","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":"Selecting Optimal Path in Multiple-Path Routing for MANETs Using Fuzzy Cost","authors":"N. Sasikala, K. P. K. Rao, K. Shanker","doi":"10.17485/ijst/v17i7.3006","DOIUrl":"https://doi.org/10.17485/ijst/v17i7.3006","url":null,"abstract":"Background/ Objectives: Mobile Ad Hoc Networks (MANETs) consists of a set of nodes, where the nodes tend to change their positions time to time because of their infrastructure less characteristic. In MANETs, the protocol that is considered to be the appropriate for constructing an efficient route is AODV. Broadcast storm is another approach that can be used for establishing a path between the sender and receiver. Due to the concerns related to contention and collision, broadcast is not considered as an efficient mechanism for path selection. Though the aim of broadcasting is to minimize the flooding other issues like bandwidth consumption, collision and contention cannot be controlled. Since MANETs are associated with inadequate bandwidth, the approach of broadcasting is not efficient. Multipath routing approach permits in constructing multiple paths between the communicating nodes (sender and receiver). This approach is complicated due to the problem of node mobility in MANETs. The other paths available are not reliable because of the ad hoc nature of MANETs. The intention is to design a fuzzy controller that assists in reducing the reconstruction of paths using fuzzy cost assigned to each node in the network. Methods: The concept of this paper is to establish an optimal path from sender node to the receiver node from the available multiple paths in MANETs. The path established in this approach uses fuzzy cost. Fuzzy measure is the criteria used for establishing a path. The concept ImRMR used in this paper has been included with few improvements. The basic functionality of ImRMR is that paths are classified based on rank fitness. The proposal is to classify the paths based on its fuzzy cost. This fuzzy cost classifies the paths fitness. Findings: The proposed fuzzy cost approach discussed in this study is compared with On-Demand Multicast Routing Protocol (ODMRP). The result exhibits that the proposed method works better under differing conditions like traffic load, transmission range between nodes and also considers node mobility. The proposed mechanism with inclusion of fuzzy cost shows 5% energy efficiency, reduces the collisions by about 35% and throughput is enhanced by 30%. There has been a considerable decrease in the number of queries by 23%. The simulation results indicate that ODMRP with fuzzy cost is more useful and significant. Hence, consideration of fuzzy cost as a means for selecting an effective route is assumed to be the best. Novelty: This method contributes in reducing the drawbacks of routing approaches whether it is unipath and multi-path approach. The proposed approach changes the value of the attributes for a given route with fuzzy cost. A threshold value will be considered initially and the route having a cost more than the initialized threshold would be advised as the best route. This route would be considered as the efficient route for transmission between the sender and the receiver. Keywords: Uni­path, multiple paths,","PeriodicalId":508200,"journal":{"name":"Indian Journal Of Science And Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139835635","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 Hybrid Approach to Analyse the Public Sentiment on Covid-19 Tweets","authors":"Radha Krishna Jana, Dharmpal Singh, Saikat Maity, Hrithik Paul","doi":"10.17485/ijst/v17i7.3017","DOIUrl":"https://doi.org/10.17485/ijst/v17i7.3017","url":null,"abstract":"Objectives: The objective of this study is to introduce a hybrid model for analyzing the people sentiment on covid-19 tweets. Methods: We used a total no. of 27,500 datasets, 70% of the data sets for training and reserved the other 30% for testing. Due to this separation 19,250 samples are used for training, the remaining 8,250 were used to evaluate the accuracy of the test. This paper proposes a technique for sentiment analysis that integrates deep learning, genetic algorithms (GA), and social media sentiment. For more accuracy and performance, we here suggested a hybrid genetic algorithm-based model. A hybrid model is created by assembling the LSTM model and providing it to the genetic algorithm architecture. Findings: LSTM with a genetic model better than LSTM without genetic model. The accuracy of our suggested model is 96.40%. Novelty : The accuracy of the LSTM model for sentiment analysis is 91%. The accuracy of the proposed model is 96.40%. The proposed model is more accurate for sentiment prediction. Keywords: Social network perception, Crossover, Mutation, LSTM, NLP, GA","PeriodicalId":508200,"journal":{"name":"Indian Journal Of Science And Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139836068","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":"Study of Active Medium Length Effect on Characteristics of Passive QSwitching and Stokes with Anti-Stokes Pulse","authors":"Dunya Saad Hussein, Abdul-Kareem Mahdi Salih","doi":"10.17485/ijst/v17i8.2823","DOIUrl":"https://doi.org/10.17485/ijst/v17i8.2823","url":null,"abstract":"Objective: To study the effect of active medium length on the characteristics of passive Q-switching pulses, Stokes pulses, and anti-Stokes pulses generated by laser-Raman medium interaction in optical systems, theoretically. Methods: The optical system consists of Nd+3:YVO4, PbWO4, and Cr+4:YAG as active mediums, Raman medium, and saturable absorber materials, respectively. The rate equations model has been used in the study, and the Rung-Kutta-Fehelberg numerical method was used to solve the rate equations. Finding: The result shows that, decreasing of the active medium length leads to emit high power pulses at advanced time. It also leads to increase in initial value and the maximum value of population inversion density, and leads to increase in the energy of passive Q-switching pulses, Stokes pulses, and anti-Stokes pulses. So the decreasing of the active medium length leads to decrease in the pulses duration and the final population inversion density. To increase the power of the three generated pulses, the length of the active medium used in the system must be decreased. Novelty: The characteristics of two pulses generated by Laser-Raman interaction (passive Q-switching pulse and Stokes pulse) have been of interest in some studies. This study investigates the effect of the active medium length on the characteristics of three pulses generated (anti-Stokes pulse with Stokes pulse as well as the passive Q-switching pulses) by the optical system rather than two pulses. Keywords: Laser; Nd+3 :YVO4; passive Q-­switching pulse; Stokes and anti-­Stokes pulses 1","PeriodicalId":508200,"journal":{"name":"Indian Journal Of Science And Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140456336","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":"Selecting Optimal Path in Multiple-Path Routing for MANETs Using Fuzzy Cost","authors":"N. Sasikala, K. P. K. Rao, K. Shanker","doi":"10.17485/ijst/v17i7.3006","DOIUrl":"https://doi.org/10.17485/ijst/v17i7.3006","url":null,"abstract":"Background/ Objectives: Mobile Ad Hoc Networks (MANETs) consists of a set of nodes, where the nodes tend to change their positions time to time because of their infrastructure less characteristic. In MANETs, the protocol that is considered to be the appropriate for constructing an efficient route is AODV. Broadcast storm is another approach that can be used for establishing a path between the sender and receiver. Due to the concerns related to contention and collision, broadcast is not considered as an efficient mechanism for path selection. Though the aim of broadcasting is to minimize the flooding other issues like bandwidth consumption, collision and contention cannot be controlled. Since MANETs are associated with inadequate bandwidth, the approach of broadcasting is not efficient. Multipath routing approach permits in constructing multiple paths between the communicating nodes (sender and receiver). This approach is complicated due to the problem of node mobility in MANETs. The other paths available are not reliable because of the ad hoc nature of MANETs. The intention is to design a fuzzy controller that assists in reducing the reconstruction of paths using fuzzy cost assigned to each node in the network. Methods: The concept of this paper is to establish an optimal path from sender node to the receiver node from the available multiple paths in MANETs. The path established in this approach uses fuzzy cost. Fuzzy measure is the criteria used for establishing a path. The concept ImRMR used in this paper has been included with few improvements. The basic functionality of ImRMR is that paths are classified based on rank fitness. The proposal is to classify the paths based on its fuzzy cost. This fuzzy cost classifies the paths fitness. Findings: The proposed fuzzy cost approach discussed in this study is compared with On-Demand Multicast Routing Protocol (ODMRP). The result exhibits that the proposed method works better under differing conditions like traffic load, transmission range between nodes and also considers node mobility. The proposed mechanism with inclusion of fuzzy cost shows 5% energy efficiency, reduces the collisions by about 35% and throughput is enhanced by 30%. There has been a considerable decrease in the number of queries by 23%. The simulation results indicate that ODMRP with fuzzy cost is more useful and significant. Hence, consideration of fuzzy cost as a means for selecting an effective route is assumed to be the best. Novelty: This method contributes in reducing the drawbacks of routing approaches whether it is unipath and multi-path approach. The proposed approach changes the value of the attributes for a given route with fuzzy cost. A threshold value will be considered initially and the route having a cost more than the initialized threshold would be advised as the best route. This route would be considered as the efficient route for transmission between the sender and the receiver. Keywords: Uni­path, multiple paths,","PeriodicalId":508200,"journal":{"name":"Indian Journal Of Science And Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139776181","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":"Microstructural and Mechanical Characterization of the Mg Based Functionally Graded Material Fabricated through Centrifugal Casting Process","authors":"M Anil Kumar, V. Srinivasan, P. R. Raju","doi":"10.17485/ijst/v17i7.2828","DOIUrl":"https://doi.org/10.17485/ijst/v17i7.2828","url":null,"abstract":"Objectives: The aim of this study is to examine the mechanical and microstructural properties of functionally graded material (FGM) composites based on magnesium (Mg). Magnesium alloys are commonly employed in the development of biomaterials for implant applications owing to their favorable corrosion properties. The research objective is to study the microstructural and mechanical properties and produce Zn/Mo reinforced functionally graded magnesium composites using the centrifugal casting. Methods: A triple layered cylindrical shaped Mg based functionally graded material (FGM) was fabricated through a centrifugal process from (Mg (80%) +Zn (10%) + Mo (10%) alloy. The developed FGMs have been analyzed for their mechanical and microstructural characteristics. The microstructure was analyzed via the OM AND SEM microscope. It is identified that denser particle molybdenum (Mo) have influenced the mechanical and microstructural characteristics. Findings: Results recommend that, all the three layered testing’s, Mg (80%) +Zn (10%) + Mo (10%) composite exhibited favorable mechanical and microstructural properties. It is identified that denser particle of Mo which is influenced the microstructural characteristics. The alteration in micro hardness in the direction of centrifugal force is observed, and it is perceived that top surface has higher hardness as compared to the middle and bottom region. The flexural strength of top surface sample is 254 MPa, which is 10% greater than middle surface sample and 12.36% greater than bottom surface sample. Compressive strength of 385 MPa, surpassing the middle surface sample by 17.11% and the bottom surface sample by 19.36%. Novelty: In this study, a novel three-layered centrifugal casting technique was devised. Owing to its rapid degradability, the anticipated duration of the implants within the human body is significantly shorter in comparison to alternative biomaterials such as Titanium and Stainless steel. Furthermore, the findings from the conducted tests strongly advocate for the utilization of this technique in biomedical implantations. Keywords: Functionally graded material (FGM), Centrifugal casting, Mechanical properties, Microstructural behavior and bioimplants","PeriodicalId":508200,"journal":{"name":"Indian Journal Of Science And Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139835932","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":"Optimal Location of EV Charging Stations in the Distribution System Considering GWO Algorithm","authors":"Sai Goutham Golive, B. Paramasivam, J. Ravindra","doi":"10.17485/ijst/v17i8.2044","DOIUrl":"https://doi.org/10.17485/ijst/v17i8.2044","url":null,"abstract":"Objectives: The transition from conventional vehicles to electric vehicles (EVs) has been significantly influenced by the current scarcity of fossil fuels and the environmental concerns surrounding greenhouse gas emissions. The exploration of the optimal location of electric vehicle charging stations has been prompted by the electrification of the transportation system and the increasing demand for EVs. Methods: One of the main challenges is the detrimental impact of improper positioning of charging stations on the power distribution network. The Grey Wolf Optimization (GWO) approach is used to determine the effective Charging Stations (CS) locations to minimize the losses, which is the major objective of the proposed technique. An IEEE 33 bus system is used to implement the suggested technique. Findings : The proposed method finds the suitable deployments for EVCS within the distribution system, which is of utmost importance due to the constraints imposed by limited battery capacity and prolonged charging periods. This article proposes the optimal location for EVCS to minimize losses inside the distribution network. Novelty: The effectiveness of the proposed GWO is evaluated by comparing it with the PSO optimal algorithm. Finally, a comparison of system voltage and nominal voltage is presented and the probability comparison of EV location with the base case and the proposed algorithms is presented. Keywords: Electric Vehicle Charging Station, Distribution System, GWO, System and Nominal Voltage","PeriodicalId":508200,"journal":{"name":"Indian Journal Of Science And Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140455353","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":"Utilizing Machine Learning for Comprehensive Analysis and Predictive Modelling of IPL-T20 Cricket Matches","authors":"Probodh Narayan Gour, Mohd. Faheem Khan","doi":"10.17485/ijst/v17i7.2944","DOIUrl":"https://doi.org/10.17485/ijst/v17i7.2944","url":null,"abstract":"Objective : Current study intends to develop a predictive model for Indian Premier League (IPL) cricket match results using machine learning techniques. In order to provide a precise framework that allows for the prediction of IPL match outcomes, it aims to examine player statistics, match dynamics, and historical data. Method : SVM, Random Forest, Logistic Regression, Decision Tree, and KNN models were used in this study to predict player performance on any given day. Form, fitness, and previous results were among the historical player data that were used as characteristics. Each model preceded through training and testing phases, with accuracy, precision, and recall metrics evaluated to determine the most effective algorithm for forecasting player performance. Findings : Final studies indicated that relative team strength of competitor teams, recent form of players, and opponent pairings are distinguishing features for predicting the performance of both players and teams on any given day. The multi-machine learning approach-based model that was constructed demonstrated an accuracy of 0.71, further indicating improved performance for the given challenge. Modelling team strength is similar to modelling individual player batting and bowling performances, which is the cornerstone of our approach. Novelty : This paper was designed based on a novel approach leveraging combinatorial machine learning methods. This has been found to demonstrate unprecedented performance improvement in predicting a player’s performance on a given day. Additionally, the presented approach may prove valuable in opening new avenues to advance machine learning applications in sports analytics by addressing the limitations of existing methods. Keywords: Machine Learning, Sports analytics, SVM, Random Forest, KNN","PeriodicalId":508200,"journal":{"name":"Indian Journal Of Science And Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139776472","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}