All machine learning procedures consume a mathematical foundation. the aforementioned is applicable to Deep learning, optimization, and any additional Statistics Science processes since Deep Knowledge is a subset of M...
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this study introduces an intelligent customer service system for urban rail transit, addressing inefficiencies and high labor costs in existing systems' problem classification and feedback mechanisms. Leveraging s...
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ISBN:
(纸本)9798350375084;9798350375077
this study introduces an intelligent customer service system for urban rail transit, addressing inefficiencies and high labor costs in existing systems' problem classification and feedback mechanisms. Leveraging semantic understanding, the system integrates advanced speech recognition, intention classification, and entity extraction to automate the processing and intelligent classification of passenger hotline calls. Post-evaluation, the system demonstrated a minimum of 4.55% enhancement in data processing accuracy and F1 score, respectively, validating its efficacy in enhancing efficiency and precision. Furthermore, the research delves into the practical application of entity recognition, offering insights into the integration of natural language processing in intelligent customer service systems.
the proceedings contain 150 papers. the topics discussed include: support vector machines principles and actually example;continuous optimization of business environment for power grid timing control;assessment of new...
the proceedings contain 150 papers. the topics discussed include: support vector machines principles and actually example;continuous optimization of business environment for power grid timing control;assessment of new energy consumption capacity of grid based on edge computing;evaluation and power grid investment efficiency under high quality development;design of real-time measurement and intelligent path selection system for network quality under big data;enterprise level data warehouse system based on hive in big data environment;research on performance prediction method based on gaussian process regression;design of information management system based on random leapfrog band selection algorithm;simulation and optimization system of automated e-commerce logistics warehouse allocation network based on intelligent algorithm;and intelligent analysis method of e-commerce data based on multiple machine learning algorithms.
Colorectal cancer is one of the most common malignant tumors globally. this study aims to construct a classification model to predict the development of colorectal cancer, and to explore the important influential vari...
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ISBN:
(纸本)9798350375084;9798350375077
Colorectal cancer is one of the most common malignant tumors globally. this study aims to construct a classification model to predict the development of colorectal cancer, and to explore the important influential variables and their interactions that affect the carcinogenesis of colorectal cancer, in order to provide more in-depth scientific evidence for the analysis, treatment and prevention of colorectal cancer. the results show that the model constructed in this study through machine learning algorithms can effectively classify and predict the development of colorectal cancer. the model has proven to be effective, convenient for practical application, and highly applicable.
this study offers new insights into the management of liver cirrhosis, serving as a vital resource for public health practitioners. the findings emphasize the importance of evidence-based treatments and enhanced colla...
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this paper focuses on the research of automatic search of machine learning models using intelligent computing technology. In the current era of big data and artificial intelligence, selecting and optimizing the right ...
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this article studies the steps of email classification, selects the Naive Bayes algorithm for email classification, uses Support Vector Machine (SVM) for multi label secondary classification, and designs corresponding...
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ISBN:
(纸本)9798350375084;9798350375077
this article studies the steps of email classification, selects the Naive Bayes algorithm for email classification, uses Support Vector Machine (SVM) for multi label secondary classification, and designs corresponding text files and libraries from the stages of data preparation and preprocessing, garbage labeling, etc. the training model is used to output prediction results and determine whether the email is spam. Using the detailed execution process of the confusion matrix, determine the proportion of the test set for this design, and design the implementation process of primary and secondary classification based on the proportion design.
To enhance the monitoring efficiency and accuracy of health and wellness environments, an intelligent eco-health environment monitoring system based on IoT technology was designed and developed. the system adopts a la...
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ISBN:
(纸本)9798400710353
To enhance the monitoring efficiency and accuracy of health and wellness environments, an intelligent eco-health environment monitoring system based on IoT technology was designed and developed. the system adopts a layered architecture and various data processing algorithms, ensuring accurate transmission and effective processing of data by real-time monitoring of key environmental parameters such as temperature, humidity, and air quality. the results indicate that the developed system can significantly improve the response speed and accuracy of environmental monitoring, providing efficient technical support for health and wellness environments.
Collaborating efficiently on medical imaging presents hurdles stemming from data privacy concerns and collaboration barriers. In response to these challenges, federated learning emerges as a decentralized machine lear...
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ISBN:
(纸本)9798400716645
Collaborating efficiently on medical imaging presents hurdles stemming from data privacy concerns and collaboration barriers. In response to these challenges, federated learning emerges as a decentralized machine learning method showing considerable promise. Its notable advantage lies in preserving data privacy robustly, enabling collaborative efforts without compromising sensitive medical information confidentiality. this study meticulously examines federated learning's application in medical imaging, thoroughly assessing its strengths and limitations. Our experimental results show that federated learning has potential in the field of medical images, achieving cooperative improvement in model performance while protecting data privacy.
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