Authors:- M.Siva Leela, Shaik Hussain Vali

Abstract-In this study, we use a loop matrix to describe the reorganisation of the RDN's formulation. Calculation time is increased when an optimum reorganisation is determined analytically. More network buses means more time to calculate. Therefore, a technique of optimisation is required to determine the best reorganisation of the radial distribution system. The optimum reorganisation aims to reduce network losses to a minimum. Genetic algorithm (GA) and particle swarm optimisation (PSO) are the optimisation methods employed in this piece. In this piece, we look at how meta-heuristic optimisation may be applied for efficient rearranging. For the purpose of rearrangement, we use organic optimisation techniques such as the PSO approach. We describe and analyse the reorganisation issue in a typical large-scale 119 and 135-node network under both optimisation and non-optimization conditions. The outcomes are then compared with one another.

DOI: 10.61137/ijsret.vol.9.issue6.117

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Authors:-Dr. Juhi Shamim

Abstract- Present paper discusses the determinants of food grains production in India. The Indian economy has changed fundamentally over time with the foreseen decrease in agriculture’s share in gross domestic product (GDP). There is high burden on agriculture to produce more and to raise the income of farmers. India’s manufacturing sector saw unpredictable growth and its share in GDP has nearly stayed steady at 15 percent over the most recent three decades. Under these conditions, it is valuable to investigate the determinants of agriculture growth. There are countless determinants that influence food grains production. Some of them are discussed in this paper.

DOI: 10.61137/ijsret.vol.9.issue6.116

Published by: vikaspatanker

 

Srinivasa Chakravarthy Seethala
Affilation:	Senior Data Engineer HCL America Inc, USA
Email-Id:	srinivasa.seethala@gmail.com
About Srinivasa Seethala has done Bachelor of Engineering in Mechanical from University of Madras. A Senior Data Engineer with over 25 years of experience, specializing in AI, Big Data, and data warehousing development. I have demonstrated expertise in designing and implementing advanced data solutions, integrating AI to enhance data quality and system performance. A recognized leader in the field, I excel at modernizing data architectures and leading cross-functional teams to deliver innovative solutions for complex challenges. As a published author with expertise in AI and Big Data, I am skilled at driving impactful projects across industries, including finance, healthcare, and e-commerce, while ensuring scalability and efficiency in data systems.
Projects & Publications: PNC Claims(Snowflake) Client: United Services Automobile Association (USAA) Project : Project OAK Client: United Technologies Corporation, USA Project : Broker Dealer Operations Reporting Client : Lincoln Financial Group, USA

 

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Demand Forecasting Using MLR-ARIMA Hybrid Model
Authors:-Vaibhav R. A. Prasad, Anunita Bhattacharya

Abstract- Data analytics (DA) is becoming increasingly important in supply chain management (SCM) due to its ability to provide valuable insights that can improve efficiency and decision-making. One of the key applications of DA in SCM is demand forecasting, which involves predicting future demand for products or services. Accurate demand forecasting is crucial for ensuring that the right amount of inventory is maintained, reducing the risk of stock outs, and optimizing production and logistics processes. There are several algorithms that can be used for demand forecasting in SCM, and they can be broadly classified into two categories: time-series forecasting and causal forecasting. Time-series forecasting algorithms rely on historical data to make predictions. This study will Evaluate both time-series and casual algorithms and study their efficacy and uses.

DOI: 10.61137/ijsret.vol.9.issue6.115

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Demand Forecasting Using MLR-ARIMA Hybrid Model
Authors:-Vaibhav R. A. Prasad, Anunita Bhattacharya

Abstract- Data analytics (DA) is becoming increasingly important in supply chain management (SCM) due to its ability to provide valuable insights that can improve efficiency and decision-making. One of the key applications of DA in SCM is demand forecasting, which involves predicting future demand for products or services. Accurate demand forecasting is crucial for ensuring that the right amount of inventory is maintained, reducing the risk of stock outs, and optimizing production and logistics processes. There are several algorithms that can be used for demand forecasting in SCM, and they can be broadly classified into two categories: time-series forecasting and causal forecasting. Time-series forecasting algorithms rely on historical data to make predictions. This study will Evaluate both time-series and casual algorithms and study their efficacy and uses.

DOI: 10.61137/ijsret.vol.9.issue6.115

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Relationship between Electronic Banking and Customer Satisfaction
Authors:-Shaun Mendonsa, Akash Shukla, Akash, Venkata Veda Vyas Dega

Abstract- This research paper explores the relationship between electronic banking and customer satisfaction in the banking sector of India. The main objective of this study is to investigate the impact of e-service quality on customer satisfaction in the banking sector. The study uses a mixed research approach, comprising both descriptive and analytical research. A survey consisting of 12 questions was conducted, and the responses were collected from 59 respondents. The study found that e-service quality is the most significant factor impacting customer satisfaction in the banking sector. The study concludes that banks can gain a competitive advantage by focusing on the quality of electronic banking services, which helps attract and retain a strong customer base. Limitations of the study are also discussed, and suggestions for future research are provided.

DOI: 10.61137/ijsret.vol.9.issue6.114

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Authors:-Bhavesh Gattani, Shamik Saha, Komal Gill

Abstract- In FMCG e-commerce, digital tactics are crucial in changing customer purchasing trends and behaviours. This study emphasises advertising strategies and the tactical application of consumer data as it investigates the significant effects of digital marketing and AI-driven tools on consumer patterns. By utilising cutting-edge technologies like chatbots, complex algorithms, and user behaviour analysis, businesses may gain profound insights into their clientele, facilitating customised and customer- focused online shopping experiences. This shift mostly depends on customised digital tactics that use customer data to design distinctive e-commerce experiences. This strategy also applies to advertising, using data-driven techniques to provide pertinent and compelling advertisements that are tailored to the unique requirements and tastes of FMCG customers. When it comes to FMCG e-commerce advertising, the use of digital and AI techniques has a big impact on customer engagement and purchasing behaviours. Businesses may maximise the impact of their ads by optimising the selection and delivery of their ads with the help of these tools’ insights. This study examines the impact of digital strategies on FMCG e-commerce customer behaviours by combining consumer data with insights from these strategies. Interestingly, these tactics—which are especially noticeable in social media postings and pop-up advertisements—stimulate instant wants, enable interactive interfaces, and encourage higher spending in the FMCG e-commerce space.

DOI: 10.61137/ijsret.vol.9.issue6.113

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Authors:-Nripendra Singh, Himanshi Sankhla, Lalit Singh, Vartika Mudgal

Abstract- In the contemporary landscape of financial services, the convergence of finance and technology has ushered in a transformative era, prominently manifested in the phenomenon of Open Banking. This study seeks to unravel the intricate dynamics between finance and technology and their collective influence on the swift evolution of Open Banking.
The research engages in a comprehensive exploration of the symbiotic relationship between finance and technology, examining how technological innovations act as catalysts for financial sector advancements. Emphasizing the pivotal role of digitalization, artificial intelligence, block chain, and other cutting-edge technologies, our investigation delves into their collaborative impact, fueling the rapid expansion and adoption of Open Banking models across the global financial ecosystem.
Furthermore, the study critically analyses the implications of Open Banking on traditional financial institutions, fintech disruptors, and, most importantly, the end-users. Through empirical evidence and case studies, we aim to illuminate the tangible benefits and challenges posed by this paradigm shift, shedding light on how Open Banking fosters competition, enhances financial inclusion, and redefines customer-centric financial services.
The findings of this research not only contribute to the academic understanding of the subject but also offer valuable insights for industry stakeholders, policymakers, and practitioners. By elucidating the synergistic dynamics of finance and technology in the context of Open Banking, this study provides a roadmap for navigating the evolving financial landscape, fostering innovation, and ensuring a resilient and inclusive financial future.

DOI: 10.61137/ijsret.vol.9.issue6.112

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Authors:-Madhur Narang, Kushagra Sahani,Asso. Prof. Dr. Neha Agrawal, Asst. Prof. Ms. Meenu Garg

Abstract- The stock market is the platform where anyone can buy and sell or trade shares of public companies, and for that predicting the stock price helps us to forecast the future value of the company shares, derivatives, and mutual funds. So, while doing predictions of the stock market we have to keep some key points in our mind such as No one can accurately predict the future movement of the stock market because the stock market is a composite and volatile system, and many factors can affect its performance.
To evaluate a company’s financial stability and performance, fundamental analysis is used. On the other hand, for reviewing historical price and bulk data, technical analysis has been carried out to recognize tendencies and patterns. Risk management, while investing in the stock market carries inherent risks, and to mitigate those risks, it is crucial to spread out investments and establish stop-market orders, and other techniques.
The aim of this paper is to suggest deep learning techniques in order to predict the stock prices of different companies such as AAPL(Apple), BAM (Brookfield Asset Management), and UBER and using two different models such CNN (Convolutional Neural Network) in CNN the paper uses One -Dimensional CNN (1D CNN) and LSTM (Long Short-Term Memory) uses Bidirectional LSTM.

DOI: 10.61137/ijsret.vol.9.issue6.111|

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Authors:- Geofrey Mwamba Nyabuto

Abstract- The Internet as loosely defined, is a network of networks (Kumar & Deepa, 2015). Behind these networks are many social and economic opportunities that have become key enablers on many fronts. It is through the Internet that social media has become a possibility and whose use has directly or indirectly led to either the inclusion or exclusion of individuals from one or more aspects of social life. With inclusion, the use of social media has ensured that individuals have equal opportunities, access to resources and chances of participation regardless of their background and location. On the other hand, in exclusivity, social media or the Internet denies some of its users a chance to be part of the bigger picture due to one or more reasons.
This paper does a systematic review of the literature on the Internet, what it is and the different theories that seek to explain its originality or existence. The paper also reviews social media as a product of the Internet and how it has been used to enhance inclusivity and exclusivity in the same measure. It further discusses some of the contributions social media has made to societies as well as how it has been used to enhance inclusion and exclusion. With examples, the paper shows how social media has been incorporated and become part of our normal life. Lastly, it summarizes some of the strategies that can be implemented to minimize exclusion and how society plays a pivotal role in achieving this.

DOI: 10.61137/ijsret.vol.9.issue6.110

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