In order to overcome the problems existing in traditional financial risk evaluation methods, such as high generalization error and fitting degree with actual value, this paper designs a financial risk evaluation metho...
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In order to overcome the problems existing in traditional financial risk evaluation methods, such as high generalization error and fitting degree with actual value, this paper designs a financial risk evaluation method of blockchain digital currency based on cart algorithm. After screening and ranking the financial risk indicators of blockchain digital currency, the financial risk level of blockchain digital currency is determined by combining cart algorithm. Finally, by calculating the covariance matrix of the financial risk decision matrix, the positive ideal solution and the negative ideal solution of the financial risk are found, and then the final evaluation result is obtained by combining the progress of the financial risk. Experimental results show that the minimum generalization error of this method is only 0.021, the fitting degree of the obtained results and the actual risk can reach 98.0%, and the maximum risk accuracy can reach 0.978.
International trade, as an important component of economic exchange between countries, is of great significance for the economic development of each country and international cooperation. In international trade, the s...
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International trade, as an important component of economic exchange between countries, is of great significance for the economic development of each country and international cooperation. In international trade, the selection and evaluation of suppliers has always been a key issue. To ensure the smooth progress of trade and the controllability of quality, it is necessary to establish a target supplier evaluation system. This article used the cart (Classification and Regression Tree) algorithm to help identify and analyze the impact of key factors on supplier evaluation and classify and evaluate suppliers. The international trade target supplier evaluation system based on the cart algorithm was also constructed, and its performance was tested in the experimental section and compared with the international trade target supplier evaluation system based on traditional algorithms. According to the experimental results, it can be concluded that both the traditional algorithm and the cart algorithm performed well in terms of application effectiveness and system user satisfaction. In terms of application effectiveness, the average score of traditional algorithms was 4.3, with a rating range of 3.8 to 4.9, while the average score of the cart algorithm was 4.6, with a rating range of 4.2 to 5.0. The satisfaction rating of system users on the cart algorithm was slightly higher than that of traditional algorithms, indicating that the cart algorithm has better application effectiveness and user satisfaction in the design of international trade target supplier evaluation systems. The design of an international trade target supplier evaluation system based on the cart algorithm can also help enterprises reduce trade risks and improve the stability and reliability of the supply chain. It has important practical significance and application value for further promoting the development of international trade.
This paper mainly focuses on teenagers under the age of 15 to conduct experimental tests to study their physical and psychological responses when using new media art works, just as dopamine, heart rate, eye tracking, ...
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ISBN:
(纸本)9798350375343;9798350375336
This paper mainly focuses on teenagers under the age of 15 to conduct experimental tests to study their physical and psychological responses when using new media art works, just as dopamine, heart rate, eye tracking, brain wave monitoring, etc., to analyze user residence time and preferences. Then through questionnaire survey, in-depth interviews and other ways to obtain users' experience feedback on new media art works, to understand the user's cognitive, emotional, behavioral and other experience of art works. Analyze the interaction process between users and new media art works, explore the interactive relationship between users and products, and understand users' engagement, emotional input and other experiences. New technology just as the cart algorithm and AIGC is then used to process the data to ensure the reliability and validity of the experimental samples. The construction of the experimental model should also consider the requirements of minimum cost, minimum manpower, minimum time, maximum coverage, etc. The construction of the experimental model is a process of gradual improvement. The new media art model is optimized according to the needs of users, ensuring that users of the same group are trained in different time periods, and modifying the model in real time. After comparing the data of the three types of theme model tests, the model with the highest score and the lowest modification rate is the best solution.
Predicting client churn in telecommunication industries becomes the most significant topic for analysis in recent years. Because its helps in detecting which customer are likely to change or cancel their subscription ...
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ISBN:
(纸本)9789811500299;9789811500282
Predicting client churn in telecommunication industries becomes the most significant topic for analysis in recent years. Because its helps in detecting which customer are likely to change or cancel their subscription to a service. Analysis of information that is extracted from telecommunication companies will help to seek out the explanations of client churn and also uses the knowledge to retain the purchasers. Thus, predicting churn is extremely necessary for telecommunication firms to retain their customers. During this paper, we have designed the classification model using call tree, evaluated the performance measures, and compared its performance with logistic regression model.
Nowadays, with the coming of education informatization, MOOC is developing vigorously. Accumulating a large n umber of students' behavior data in the online teaching platforms has been widely concerned. In this pa...
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ISBN:
(纸本)9781538674130
Nowadays, with the coming of education informatization, MOOC is developing vigorously. Accumulating a large n umber of students' behavior data in the online teaching platforms has been widely concerned. In this paper, using the cart algorithm of decision tree, we analyze the data of MOOC about medical science in Stanford University. And then we explore the factors and importance influencing the test results. The study found that the total number of questions, the score of assignments, and the number of quizzes could be used as an important indicator of performance prediction. We also found that the decision tree model constructed by this course is as accurate as 90%, and the value of cart algorithm for online learning effect is tested. Finally, based on the related research of Stanford University, the paper puts forward some suggestions to improve the service mode of MOOC platforms.
In this paper, the information push service will be studied to realize the customization of messages according to precise space-time and crop message, and the meteorological message, monitoring data and decision-makin...
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ISBN:
(纸本)9781728126326
In this paper, the information push service will be studied to realize the customization of messages according to precise space-time and crop message, and the meteorological message, monitoring data and decision-making model of the designated area in a specific time will be combined to decide whether to apply fertilizer and the amount of fertilizer. The push technology will be combined according to the decision tree based on cart algorithm for sample set to verify and make decision on information and the push server based on XMPP protocol will be built to recommend decision information for users automatically and intelligently. The farm operation database is established to push the farm operation information to different regions on a time scale, which directly guides the actual production of users and ensures the timeliness of information and high efficiency of management.
Up to now, the common method of reservoir well group that is dynamic connectivity, it mainly includes tracer testing, stress testing, well testing, and numerical simulation. The implementation of these methods is more...
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ISBN:
(纸本)9783038350125
Up to now, the common method of reservoir well group that is dynamic connectivity, it mainly includes tracer testing, stress testing, well testing, and numerical simulation. The implementation of these methods is more complex, expensive, high cost, and will affect the normal production of the oilfield. Because of the convenient injection and dynamic data it can get convenient. This paper presents a method that using dynamic reservoir development data inverse well group connectivity. cart algorithm analysis and extraction of potential knowledge from the oilfield development. It establish direct mapping of logging data and well group connectivity relationship. Experiments show that using dynamic data to study well group connectivity relationship can greatly reduce the cost and as a result has a higher accuracy.
The increasing demand for electricity and the imperatives of climate change have made the optimization of power system planning critical for the energy transition and grid efficiency. This study presents an innovative...
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The increasing demand for electricity and the imperatives of climate change have made the optimization of power system planning critical for the energy transition and grid efficiency. This study presents an innovative planning method for inter-regional AC-DC hybrid power systems, leveraging the Classification and Regression Tree (cart) algorithm to optimize the operational characteristics of direct current (DC) channels. By designing a closed-loop iteration, precise operational constraints are considered by the cart algorithm, which immerged into the planning model to achieve safe and economic optimization. Based on the empirical analysis of the HRP-38 system, this study concludes that the cart algorithm offers a constructive approach to managing the operational complexities of modern power grids. By optimizing and refining DC operational characteristics based on actual system requirements, the algorithm contributes to improvements in safety, economic efficiency, and environmental sustainability within the confines of the HRP-38 node system. Consequently, the effectiveness of the cart optimization approach could be corroborated. Meanwhile, this study also acknowledges the limitations in generalizing these results to other power grid configurations and the need for further exploration in developing environmentally conscious planning methods.
In this article, I consider whether certain attributes of a judge and, most importantly, the interaction effects of these characteristics affect the way judges decide cases and can explain disparities in sentencing ou...
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In classification, a decision tree is a common model due to its simple structure and easy understanding. Most of decision tree algorithms assume all instances in a dataset have the same degree of confidence, so they u...
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In classification, a decision tree is a common model due to its simple structure and easy understanding. Most of decision tree algorithms assume all instances in a dataset have the same degree of confidence, so they use the same generation and pruning strategies for all training instances. In fact, the instances with greater degree of confidence are more useful than the ones with lower degree of confidence in the same dataset. Therefore, the instances should be treated discriminately according to their corresponding confidence degrees when training classifiers. In this paper, we investigate the impact and significance of degree of confidence of instances on the classification performance of decision tree algorithms, taking the classification and regression tree (cart) algorithm as an example. First, the degree of confidence of instances is quantified from a statistical perspective. Then, a developed cart algorithm named C_cart is proposed by introducing the confidence of instances into the generation and pruning processes of cart algorithm. Finally, we conduct experiments to evaluate the performance of C_cart algorithm. The experimental results show that our C_cart algorithm can significantly improve the generalization performance as well as avoiding the over-fitting problem to a certain extend.
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