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Construction of intelligent Financial Management Platform Based on Hierarchical Inheritance Algorithm

Construction of Intelligent Financial Management Platform Ba...

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Electronics and Devices, Computational Science (ICEDCS), international conference on

作者： Yanjun Geng School of Accounting Anhui Business and Technology College Hefei China

The Hierarchical Inheritance Algorithm (HGA) is an optimization technique inspired by biological principles of natural selection and heredity. This approach is versatile, finding applications in fields such as combinatorial optimization, machine learning, adaptive control, and more. It stands as a cornerstone in the realm of intelligent computing. This study bridges the gap between information technology and progressive management methodologies, aiming to adapt outdated financial management strategies to the demands of a digitalized environment, thereby pioneering a centralized financial management paradigm in the digital realm. The focus of this paper is to explore this digitally-centered financial management framework and propose a design tailored to the online ecosystem. Our findings indicate that the concept of smart finance goes beyond a mere blend of "AI and finance." Implementing its technologies involves a unique methodology that thrives on "closed-loop thinking." By gleaning insights from AI applications in diverse sectors, we've outlined the foundational pillars of smart finance application: digital transformation of specialized financial operations, algorithms rooted in financial logic that are fine-tuned through iterations, the fusion of data analytics within financial operations leading to product-centric solutions, and achieving a significant 90.00% platform integration for these smart financial solutions. As artificial intelligence technology continues to evolve, financial management will undoubtedly gravitate towards being instantaneous, user-centric, and intelligent. This will usher in heightened efficiency and benefits, heralding a new age in financial management.

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intelligent Automation in Stock Market Prediction: A Survey of Automated Models

Intelligent Automation in Stock Market Prediction: A Survey ...

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smart Technologies in computing, Electrical and Electronics (ICSTCEE), international conference on

作者： Anirudhan Adukkathayar C Vishwanath R Hulipalled Jay Bharthish Simha Ramesh Chundi REVA University Bangalore India School of Computing and Information Technology REVA University Bangalore India Abiba Systems CTO and RACE Labs REVA University Bangalore India School of Computer Science and Applications REVA University Bangalore India

ISBN: (数字)9798350384628

ISBN: (纸本)9798350384635

In an era marked by global digitization, the landscape of stock market prediction has undergone a transformative shift, ushering in a new era of technologically-driven trading. With soaring market capitalization, stock trading has emerged as a focal point for financial investment. Analysts and researchers have pioneered tools and methodologies to anticipate stock price movements, empowering investors in making informed decisions. Advanced trading models now harness unconventional textual data from social platforms, leveraging cutting-edge machine learning techniques like text data analytics and ensemble methods to significantly enhance prediction accuracies. Despite these advancements, the dynamic, erratic, and often chaotic nature of stock market data continues to present formidable challenges. This study elucidates the systematic application of machine learning-based approaches and sentimental analysis approaches for stock market prediction, grounded in a versatile framework. A critical analysis of findings from the reputable digital libraries and databases including ACM digital library and Scopus, forms the cornerstone of this inquiry. Moreover, an expansive comparative analysis was conducted to delineate key trends and significant directions. This comprehensive exploration aims to furnish budding researchers with a foundational understanding of this burgeoning domain and pave the way for further inquiry into promising avenues.

关键词： Surveys intelligent automation Analytical models Systematics Predictive models Market research Libraries

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A Microservice-based Approach to Facilitate Multi-Services in smart Space 7

A Microservice-based Approach to Facilitate Multi-Services i...

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7th international conference on Big data and Information analytics, BigDIA 2021

作者： Sun, Jie Jin, Ming Wang, Yang Shenzhen Institutes of Advanced Technology University of Chinese Academy of Sciences Shenzhen China

ISBN: (纸本)9781665424660

smart space refers to the integration of compute resources, information equipment and multi-modal sensing devices in the work or living space so that diverse services can be shared between different users in a smart way. Such a form of pervasive computing can not only make compute resources and information services universally available in such a way suitable for people's special uses but also bridge the digital information space and the physical world. However, given the properties of the smart space-each service with different resource requirements and goals, the smart space could cause resource conflicts in uses between different services and participants, and thus lead to the resource contention. In order to solve this problem while fulfilling the requirements of variable services in the smart space, in this paper, we leverage the concept of microservice to propose a universal resource scheduling and a process-evolution method for multiple concurrent services in the smart space. At the same time, to ensure that the microservice-based method is easy to implement, we also design a corresponding scheduling architecture based on the docker engine, which can functionally decompose application into a set of collaborative services. Finally, we carry out a experiment to show that the proposed architecture can achieve reasonable resource allocation, resolve resource contention, and exhibit the virtue of closed loop within different scenes and cross-scenario linkages. © 2021 IEEE.

关键词： Information services

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The Future with Advanced analytics: A Sequential Analysis of the Disruptive Technology’s Scope 20th

The Future with Advanced Analytics: A Sequential Analysis of...

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20th international conference on Hybrid intelligent Systems, HIS 2020 and 12th World Congress on Nature and Biologically Inspired computing, NaBIC 2020

作者： Varsha, R. Nair, Siddharth M. Tyagi, Amit Kumar Aswathy, S.U. RadhaKrishnan, R. School of Computer Science and Engineering Vellore Institute of Technology Chennai Campus ChennaiTamil Nadu600127 India Center for Advanced Data Science Vellore Institute of Technology ChennaiTamilnadu600127 India School of Computer Science and Engineering Vellore Institute of Technology ChennaiTamilnadu600127 India Department of Computer Science Jyothi Engineering College ThrissurKerala India Department of Civil Engineering Mangakam College of Engineering Kottayam India

ISBN: (纸本)9783030730499

Today every application like e-healthcare, agriculture, etc., is connected through smart devices to reduce workforce and enhance productivity. Many applications like defences, banking an utilities, media and entertainment, transportation, banking, retail, agriculture, education, manufacturing, etc., are using smart devices in their working-structure to improved growth of a business/production. These applications are generating a lot of data, which called as "big data" and this data is increasing at a huge rate. For example, most of the data (90%) is generated in last decade only. Together this, we required modern tools to analyses this data for generating useful results. But in near future, this analytics process may shift towards automation. How these automated analytics by deep learning (by robots/machines) will change future forever. Also, with this automated/advanced analytics process we need to provide a disruptive environment which is more towards to protecting nature. This article provide detail explanation regarding "how machines can be useful in learning process through its automate learning process" and "how machine/Artificial Intelligence (AI) can be useful in detecting vulnerabilities/intrusion without much human interaction instantly" and so on. In 21st century, most of tasks will be completed by machines or artificial intelligences. This work discusses several useful terms, scenarios (with many examples in several applications), tools, open issues with opportunities towards automated analytics, i.e., with discussing that "How AI will change near future". © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Big data

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Analysis on Stock Market Stream data Using Kafka, AWS and PowerBI 3rd

Analysis on Stock Market Stream Data Using Kafka, AWS and Po...

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3rd international conference on Machine Intelligence and smart Systems, MISS 2023

作者： Baseer, K.K. Siva Siddartha Reddy, B. Vishnuvardhan, D. Chandravathi, K. Abhishek, L. Karthikaa, M. Tirupati India Department of Information Technology Sree Vidyanikethan Engineering College Tirupati India

ISBN: (纸本)9783031691140

Real-time data analysis is becoming increasingly important, as it allows businesses to act quickly and with greater decision accuracy. Traditionally, data analysis occurs after data has been collected and saved, but real-time data analysis provides an opportunity for businesses to extract valuable insights from data as it’s generated. A streaming platform like Kafka is necessary to handle the constant intake of data in a systematic and efficient way, and to build data pipelines that reliably integrate and transfer information between platforms. Cloud computing services like AWS S3, AWS Crawler, AWS Glue data Catalog, and AWS Athena can be used in conjunction with Kafka to process and analyze the data. This framework is useful for processing real-time data in various sectors, such as the Stock market, e-commerce applications, gaming, and more, and extracting useful features and hidden patterns. Machine learning models can also be trained on the data for better analysis and *** enhance this framework, it’s important to integrate various cloud computing services with Kafka more seamlessly to better handle large-scale data. Additionally, real-time data visualization tools could help generate insights and provide interactive feedback on data streams. The incorporation of predictive analytics capabilities and intelligent, data-driven decision-making processes could help businesses make more informed decisions. By integrating real-time data analysis with intelligent automation tools, human error can be reduced, and overall efficiency and effectiveness in the decision-making process can be improved. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Marketplaces

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Machine Learning Techniques and computing Technologies for IoT based smart Healthcare (COVID-19 Case Study) 3

Machine Learning Techniques and Computing Technologies for I...

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3rd international conference on Advances in computing, Communication Control and Networking, ICAC3N 2021

作者： Mir, Mahmood Hussain Jamwal, Sanjay Islam, Shahidul Khan, Qamar Rayees Baba Ghulam Shah Badshah University Department of Computer Sciences Jammu and Kashmir Rajouri India

ISBN: (纸本)9781665438117

The exponential growth of smart devices and gadgets connected to the Internet of Things (IoT) produces massive amounts of data. The number of internet-connected devices is predicted to outnumber people by 25 to 50 billion by 2025. The new concept IoT refers to the combination of wired and wireless embedded communication technologies, sensors, actuators (transducers), and internet-connected items. The data generated by these IoT devices is in high velocity, variety, and varsity in accordance with location and time. IoT is generating data so it one of the primary sources of big data. intelligent analysis and processing need an hour to develop smart IoT applications to tackle this huge volume of data. This article accesses various computing frameworks such as Cloud computing, Fog computing and Edge computing environments for smarter IoT applications. This article also presents how machine learning algorithms can be incorporated in IoT data to get better insights. Various machine learning algorithms are explained and how these algorithms can be applied to data to get a higher level of information. This studies key contribution is how computing frameworks can be integrated with machine learning techniques in the healthcare sector to get better insights from the data. Mostly in this article, IoT and machine learning algorithms are discussed with respect to COVID-19. Moreover, the potential application areas and open issues of IoT data analytics and Machine Learning are discussed. © 2021 IEEE.

关键词： COVID-19

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Design and Development of an Efficient Traceability System for Greek Kiwifruit 10

Design and Development of an Efficient Traceability System f...

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10th international conference on Information and Communication Technologies in Agriculture, Food and Environment, HAICTA 2022

作者： Margariti, Spiridoula V. Salmas, Dimitris Pachoulas, George Schismenos, Paraskevas Baltzoi, Penelope Fotia, Konstantina Karipidis, Charalampos Tsirogiannis, Ioannis L. Stylios, Chrysostomos Laboratory of Knowledge and Intelligent Computing Department of Informatics and Telecommunications University of Ioannina Kostaki Arta47100 Greece University of Ioannina Department of Agriculture Arta47100 Greece Industrial Systems Institute Athena R.C. Platani PatrasGR26504 Greece

It is vital to establish and use a traceability system in the fresh supply-production chain. It is a consumer requirement, a useful tool for farmers to add value to their products and a single way to ensure the quality of food products. Nowadays, traceability systems incorporate Information and Communication Technologies (ICT), such as IoT, cloud computing and Big data, aiming to provide cost-effective production and traceability functionalities. IoT and cloud computing cover a range of different technologies that can be used to satisfy traceability requirements and facilitate rational decision making. In this work, we exploit the capabilities of these technologies and propose a smart traceability framework for kiwifruit. We design, develop, and apply the proposed scheme to a Greek kiwifruit farming. The results show that traceability requirements for transparency, safety and quality are satisfied. Moreover, this implementation provides meaningful insights related to intelligent fresh fruit traceability. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 international (CC BY 4.0)

关键词： Internet of things

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ChatGPT-Powered Robot: smart, Interactive Living and Bridging the Future of Education and Entertainment

ChatGPT-Powered Robot: Smart, Interactive Living and Bridgin...

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Sustainable computing and smart Systems (ICSCSS), international conference on

作者： Kaushalya Thopate Mayuri Gawade Ketaki Shirbhavikar Mukund Kulkarni Shilpa Lambor Krishna Nilesh Jaiswal Computer Engineering Vishwakarma institute of Technology Pune India Artificial Intelligence and Data Science Vishwakarma institute of Technology Pune India Mechanical Vishwakarma institute of Technology Pune India Electronics & Telecommunication Vishwakarma institute of Technology Pune India

ISBN: (数字)9798350379990

ISBN: (纸本)9798350391558

Presenting a ground-breaking robotic system that introduces remarkable control mechanisms, encompassing Bluetooth connectivity, voice commands, and gesture inputs. This technological innovation transcends conventional boundaries, characterized by its remarkable capacity to provide precise and intelligent responses to inquiries, a feat attributed to its robust data analytics capabilities harnessed through the integration of ChatGPT. The robot's loudspeaker and microphone facilitate verbal communication, while its range of sensors, including a camera, microphone and accelerometer, enable it to understand its surroundings and interact effectively with users. With ChatGPT and a web API connection for rigorous testing, this robot provides accurate answers on a wide range of topics. Although still in the development stage, it has unlimited potential to become a valuable asset in many fields, including education and entertainment. Future upgrades may include language translation, home automation, and appointment scheduling. Moreover, a major challenge faced by this voice-activated robot is accurately interpreting diverse Indian English accents and dialects in noisy environments, which can lead to misrecognition and reduced interaction effectiveness. Explore this innovative robotic device that can be conveniently operated via Bluetooth, voice commands, and gestures. Its capabilities extend to answering queries through ChatGPT and providing insightful responses by analyzing data. While the robot is still in its development phase, it has the potential to become a valuable asset for entertainment, education and beyond. Other enhancements can be added, such as language translation, home automation, and assistance with scheduling appointments or shopping. The main motive behind this project is to help ungraduated people and to provide entertainment and learning purposes for students who are developing any kind of robot.

关键词： Bluetooth Home automation Torque Education Entertainment industry Chatbots Servers

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Path Choice of smart City Construction from the Perspective of Economic Growth

Path Choice of Smart City Construction from the Perspective ...

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international conference on Machine Learning and Big data analytics for IoT Security and Privacy, SPIoT 2020

作者： Chi, Lingyu Department of Economics Shanghai University Shanghai China

ISBN: (纸本)9783030627454

As an important part of economic development, urban construction can’t be ignored in economic development. Technology plays an important role in the construction of smart cities. It is undeniable that under the technological innovation model of China, policies have a limited effect on economic development. How should China’s future smart city economic development policy be formulated? By establishing a theoretical model, it is found that when technological innovation models include imitative innovation, policies have a limited effect on economic growth. The theoretical model shows that the horizontal effect of factor accumulation cannot be ignored in the policy formulation process, but the policy direction should be changed from the past "quantity" to "quality", that is, to improve the efficiency of capital and population utilization in cities. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： smart city

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Application of smart Retail Mode in ***

Application of Smart Retail Mode in ***

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international conference on Machine Learning and Big data analytics for IoT Security and Privacy, SPIoT 2020

作者： Zhai, Jinzhi Liaoning Vocational Technical College of Modern Service ShenyangLiaoning China

ISBN: (纸本)9783030627454

The core connotation of "smart retail" is to use Internet and Internet of Things technologies to feel consumption habits, predict consumption trends, guide production and manufacturing, and provide diversified and personalized products and services for consumers. smart retail has realized the deep integration of real industries and new technologies, which breaks the situation of unilateral development online and offline. According to the actual needs of consumers, it has injected new vitality into the development of traditional retail through the mode of online and offline integration. Taking *** as the research object, this paper analyzed the main problems faced by the application of smart retail mode, and put forward feasible development paths to promote the long-term development of China’s traditional retail industry. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Sales

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