2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)最新文献_第6页

Algorithm Analysis of VaR for Financial Market Risk Based on Optimized BP Neural Network 基于优化BP神经网络的金融市场风险VaR算法分析

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10150592

Qingrui Tai

{"title":"Algorithm Analysis of VaR for Financial Market Risk Based on Optimized BP Neural Network","authors":"Qingrui Tai","doi":"10.1109/ICDCECE57866.2023.10150592","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10150592","url":null,"abstract":"VaR (Value at Risk) is an important tool for predicting and preventing financial risk, and it is also a widely used method for quantitatively measuring financial risk internationally. Due to the spontaneity and disorderly nature of financial markets, there are many complex and difficult problems in forecasting. The BP neural network analysis method, which is also non-linear, can be used to extract financial information through modelling, thus making financial theory more relevant. However, disadvantages of BP neural networks include excessive arbitrariness, slow convergence rate, local optimality and the need to optimise them in order to improve the accuracy of financial risk prediction. In this paper, the shortcomings of BP neural networks are taken into account and genetic algorithms will be used to optimise their specification. It is also combined with the VaR algorithm model to change the dynamic impact of the BP neural network subjected to random perturbation terms. Finally, a BP neural network financial warning model is established and brought into the current month CSI 300 index for forecasting. The experimental simulation results show that the optimised BP neural network is capable of faster convergence, greater stability and higher accuracy in financial alerting. In this paper, by optimizing the training algorithm of BP neural network, the ability of neural network to fit financial market related data is improved, thereby more accurately predicting market fluctuations. By combining VaR theory with neural network models, a new financial market risk VaR algorithm is established, which has high accuracy and practicality. Based on the above achievements, the financial market risk VaR algorithm based on optimized BP neural network has been widely used in the financial field, providing scientific and reliable algorithm support for financial market transactions and risk management.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128980885","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}

引用次数: 0

Deploy Machine Learning Model for Effective Bank Telemarketing Campaign 利用机器学习模型进行有效的银行电话营销活动

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10150462

M. Subramanian, Shankar Nayak Bhukya, R. Vijaya Prakash, K. N. Raju, Samrat Ray, Manikandaprabu Pandian

{"title":"Deploy Machine Learning Model for Effective Bank Telemarketing Campaign","authors":"M. Subramanian, Shankar Nayak Bhukya, R. Vijaya Prakash, K. N. Raju, Samrat Ray, Manikandaprabu Pandian","doi":"10.1109/ICDCECE57866.2023.10150462","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10150462","url":null,"abstract":"Marketing is a strategy that brings goods and services to all kinds of people. Most of the time marketing is not done to target the audience but to everyone to increase the chance of people opting for that particular product or service. Organizations use various marketing techniques like social media, telemarketing, advertisements, etc. The banking industry frequently chooses to speak with the user directly. The majority of the time, the customer hangs up as soon as they realize it was a telemarketing call because they are irritated. This is a result of a lack of essential client information. A deep learning model that analyses numerous parameters and forecasts whether a person is in a position to choose a loan or deposit money in the bank was developed to address this issue. For this purpose, a database of various parameters that the individual's demands depend on is compiled from Kaggle. On this dataset, several preprocessing approaches are then used. The procedures involve the elimination of missing values, category characteristics, outliers, undesirable features, and data balancing. To produce three machine learning (ML) models, three different techniques were applied. For this, the linear regression algorithm, the K-nearest neighbor algorithm, and the random forest (RF) algorithm are employed. To find the best algorithm for calling-list filtering, this is done. The results of testing these ML models using the preprocessed dataset are next analyzed. According to the results of the analysis, the RF algorithm is the best among the three algorithms. The RF algorithm's accuracy is somewhat more than 95%, which is higher than many other algorithms currently in use. In the future, the algorithm can be used as the backend process for a website or an application.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129008131","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}

引用次数: 1

Reducing Unwanted Service Utilization Based On Invariant Slide Window Feature Selection Using Feed Forward Nueral Network in Cloud Server Utilization 云服务器利用中基于前馈神经网络不变滑动窗口特征选择的无用服务利用率

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10151112

Savinderjit Kaur

引用次数: 0

The Intelligent Development of Smart Transmitter Estimation in Mobile Ad Hoc Network 移动自组网中智能发射机估计的智能化发展

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10150862

Hannah Jessie Rani R, R. Rajat

引用次数: 0

Design and Implementation of Smart Livestock Security System 智能家畜安全系统的设计与实现

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10150783

J. J, Lakshmi Manasa B, Niranjana C, V. K, Divakara M, Sruthi P V

{"title":"Design and Implementation of Smart Livestock Security System","authors":"J. J, Lakshmi Manasa B, Niranjana C, V. K, Divakara M, Sruthi P V","doi":"10.1109/ICDCECE57866.2023.10150783","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10150783","url":null,"abstract":"Exterior fencing is a long-term investment for cattle farm or Livestock. Physical fences help to protect cattle with latest IoT sensors. Biosecurity prevents reducing the spread of harmful diseases to cattle farm. IoT has changed the agricultural industry to next level. A topographical safety zone for cattle system is saved by the IoT sensors. Livestock monitoring, which was carried out manually using physical fences, has now been improved by using modern technology where they can be automatically tracked and monitored. IoT cattle tracking software provide a lot of benefits and security features that can acutely improve your livestock operations. The position of cattle can be easily tracked by Navigation satellites and the Global Positioning System (GPS). Effortlessly observing the Livestock management in cattle farm without farmers is improved by latest IoT sensors. IoT sensors collect data from livestock’s location, welfare of cattle. Extensive farming system will take care of animals in some welfare domains like nutrition, health, behavior.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125515809","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}

引用次数: 0

Transient Analysis of Motor Terminal Voltage, Common Mode Voltage and Bearing Voltage in 2-level and Multilevel PWM Inverter Fed Induction Motor with Long Cable 长电缆二电平和多电平PWM逆变馈电动机端电压、共模电压和轴承电压的暂态分析

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10151023

Sharana Reddy, B. Banakara, A. Abdul Khadar

{"title":"Transient Analysis of Motor Terminal Voltage, Common Mode Voltage and Bearing Voltage in 2-level and Multilevel PWM Inverter Fed Induction Motor with Long Cable","authors":"Sharana Reddy, B. Banakara, A. Abdul Khadar","doi":"10.1109/ICDCECE57866.2023.10151023","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10151023","url":null,"abstract":"The long motor cable contributes to overvoltage and higher common-mode voltage (Vcm) at the motor terminals fed by the PWM inverter due to the voltage reflection phenomenon. Higher the Vcm, higher the induced bearing voltage (Vb) and the bearing currents. Overvoltage at the motor terminals is due to two reasons, the impedance mismatch between the cable and the motor. Another reason is the PWM inverter output pulses travel at approximately half the speed of light. If the output pulses take longer than 1/3rd of the pulse rise time, voltage reflection occurs. The rise time of the inverter output pulses can be increased by using multilevel inverters. Hence, the magnitude of motor terminal voltage, Vcm, Vb is reduced significantly. In this paper, transient analysis of motor terminal voltage, Vcm and Vb in a multilevel inverter (MLI) fed induction motor with a long cable has been presented. The simulation modeling and analysis are carried out using MATLAB Simulink. The work presented in this paper provides the solution to improve the reliability of the ASD system for long motor cable applications and also to avoid downtime costs due to bearing failure.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126673973","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}

引用次数: 0

Machine Learning Based Intrusion Detection System for Network Security Using Self-Organizing Map 基于机器学习的自组织映射网络安全入侵检测系统

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10150881

Rahul Mishra

{"title":"Machine Learning Based Intrusion Detection System for Network Security Using Self-Organizing Map","authors":"Rahul Mishra","doi":"10.1109/ICDCECE57866.2023.10150881","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10150881","url":null,"abstract":"Machine learning techniques are widely used for detecting network attacks at the network level and the host level in a timely and automatic, to develop an intrusion detection system (IDS) for grading. Malicious attacks are always the need for change and scaling solutions, because it occurred during a very large volume, however, a number of challenges will occur. There is a data set that can be publicly available for further research on another malware of cyber security within the community. Network, plays an important role in modern life, has become the network security is an important field of research. Is an important network security technology Intrusion Detection System (IDS) being to monitor the software running on the network and hardware status. Despite the decades of development, the existing IDS, still, to reduce the improved error rate detection accuracy, are faced with the challenge of detecting unknown attacks. To overcome the issues proposed the method is Self-Organizing Map (SOM) Performance of intrusion detection depends mainly on the accuracy. Accuracy intrusion detection is to reduce the error rate, it must be strengthened in order to increase the detection rate. In order to improve performance, different technologies, have been used in recent works. It is the main work of the intrusion detection system for analyzing a huge network traffic data. Well-organized classification method, you need to solve this problem.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"148 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123197696","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}

引用次数: 0

Collaborative Logistics Resource Selection Mode based on Genetic Algorithm 基于遗传算法的协同物流资源选择模型

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10150578

Dan Li

{"title":"Collaborative Logistics Resource Selection Mode based on Genetic Algorithm","authors":"Dan Li","doi":"10.1109/ICDCECE57866.2023.10150578","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10150578","url":null,"abstract":"Collaborative logistics is a kind of supply chain management, involving cooperation between companies to meet customer needs. This is a complex process that requires coordination among all parties. It can be divided into three main stages: planning, implementation and monitoring. The purpose of this study is to determine the best mode of resource selection in collaborative logistics using genetic algorithms. The first stage of collaborative logistics is planning, including determining customer needs, defining inventory levels, and determining transportation routes. This is a complex process because it involves many different types of resources and products. In this paper, we will discuss how to use genetic algorithms to improve collaborative logistics. When improving the collaborative logistics process, the first thing to consider is to determine all necessary resources and products required for such supply chain management. This will help eliminate unnecessary costs, because only those items that are really needed will be purchased from suppliers. This paper analyzes the framework of collaborative logistics mechanism, uses analytic hierarchy process (AHP) to preliminarily screen logistics resources to obtain the candidate resource pool required by the collaborative system, and proposes an effective resource selection process using the improved contract network protocol method based on the collaborative logistics network model. The negotiation process determines the basic rates for transportation, warehousing, and other items in the collaborative logistics system, and achieves the aggregation and collaboration of logistics tasks through solving the collaborative logistics network model. Finally, the fuzzy comprehensive evaluation method is used to calculate the allocation proportion of additional profits in the collaborative system.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126236723","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}

引用次数: 0

Simulation Study On Photovoltaic Photothermal Coupled Ground Source Heat Pump Cogeneration 光伏光热耦合地源热泵热电联产仿真研究

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10150792

Mengfei Zhang, Jingxia Liu, Baoli Li

{"title":"Simulation Study On Photovoltaic Photothermal Coupled Ground Source Heat Pump Cogeneration","authors":"Mengfei Zhang, Jingxia Liu, Baoli Li","doi":"10.1109/ICDCECE57866.2023.10150792","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10150792","url":null,"abstract":"The TRNSYS model of photovoltaic photothermal coupled ground source heat pump cogeneration system is established in this paper. The weather data of Baotou, Inner Mongolia are used to simulate the whole year operation of the system. The influence of different cooling water flow rate and collection tank volume on power generation is analyzed. The energy consumption of energy storage systems with and without hydrogen production is analyzed and compared. It is concluded that different cooling water flow rate and different collection tank volume have little effect on the system power generation. In the heat collection season, the water temperature at the inlet of the buried pipe increases with the increase of solar radiation intensity, and the photoelectric conversion efficiency decreases with the increase of photovoltaic panel temperature. The combination of the CHP system and the hydrogen production system can absorb the discarded light and increase the energy utilization rate of the system by about 3.5%. The photovoltaic photothermal coupled ground source heat pump system is compared with the ground source heat pump system. When the ground source heat pump runs separately for heating for ten years, the soil temperature drops from the initial set of 13℃ to 1.58℃, and the temperature decreases by 11.42℃. Soil temperature decreased significantly and soil cold accumulation was serious. The photovoltaic photothermal coupled ground source heat pump system can maintain the soil temperature balance, the system runs for 10 years, the temperature only reduces 0.38℃. The COP of heat pump unit is also higher than that of ground source heat pump individual heating system.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"56 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120899414","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}

引用次数: 0

An Innovation Development of Smart Robotic System for Autonomous Monitoring 自主监控智能机器人系统的创新发展

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10150806

S. Reddy, Saurabh Kumar Srivastava

{"title":"An Innovation Development of Smart Robotic System for Autonomous Monitoring","authors":"S. Reddy, Saurabh Kumar Srivastava","doi":"10.1109/ICDCECE57866.2023.10150806","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10150806","url":null,"abstract":"Autonomous monitoring systems are becoming increasingly popular as they can be used to monitor a number of different processes and tasks, ranging from security and surveillance to industrial optimization. Smart robotic systems are one of the most popular types of autonomous monitoring systems and can provide an effective and efficient way to monitor different situations. A smart robotic system consists of a robot that is programmed and equipped with sensors to detect and recognize objects and conditions in its environment. The robot is able to analyze the data from the sensors and use it to make decisions based on its programming. This allows the robot to act autonomously and autonomously monitor different areas, depending on its programming. The advantages of using a smart robotic system for autonomous monitoring include increased accuracy, efficiency, and safety. For example, a smart robotic system can be used to monitor and control industrial processes, such as production lines and assembly lines. The sensors allow the robot to identify objects and conditions, such as temperature, humidity, and pressure, and then adjust the parameters accordingly. This can help to optimize the production process, resulting in a more efficient process.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124950919","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}

引用次数: 0