Application Of Intelligent System Research Articles

Research on the application of intelligent control system in urban landscape lighting

Research on the application of intelligent control system in urban landscape lighting

Application and Development of AI Intelligent Hospital Guidance System Based on Multimodal Large Language Model (MLLM)

Application and Development of AI Intelligent Hospital Guidance System Based on Multimodal Large Language Model (MLLM)

Design and application of intelligent teaching system for network and new media major driven by artificial intelligence technology

Design and application of intelligent teaching system for network and new media major driven by artificial intelligence technology

Application of intelligent building management system in green zero carbon building operation

Application of intelligent building management system in green zero carbon building operation

Жасанды интеллектіні Арбитражда қолданудың перспективалары

The article is devoted to the possibilities and problems of application of artificial intelligence (AI) systems in the arbitration of the Republic of Kazakhstan, i.e.: in forensic examination, analytical and organizational work, adjudication, interpretation and analysis of law, as well as control over the adoption and execution of court decisions. In the course of the research the foreign experience of using artificial intelligence systems in the judicial systems of Great Britain, the USA and the Netherlands was analyzed. In addition, three main directions of application of artificial intelligence in judicial proceedings were identified. Based on the application of artificial intelligence in practice, it was determined that the use of the European Charter of Ethics in the legislation of judicial and law enforcement systems leads, as predicted by researchers, to positive and negative consequences of use. In addition, it was determined that the use of artificial intelligence in judicial proceedings can optimize the judicial system, prevent subjective attitudes, corruption and possible miscarriage of justice, and risk is necessary. These include: compliance with the ethical principles of artificial intelligence, the impossibility of ensuring transparency and verifiability of court decisions made by artificial intelligence, their legislative non-approval and non-compliance with the requirements of law, protection of personal information. In conclusion, recommendations are given to prevent the negative impact of the introduction of artificial intelligence in arbitration.

Application of Intelligent Maintenance Management System for Urban Rail Transit Communication and Signaling

Application of Intelligent Maintenance Management System for Urban Rail Transit Communication and Signaling

Research on intelligent legal decision support system based on big data analysis

Abstract This paper constructs an intelligent decision support system using text combination feature extraction, case similarity, XBoost sentencing prediction model, and other related technologies. The performance of the smart decision support system is tested for grabbing responses and monitoring response reliability. The XGBoost algorithm is used to construct the sentencing prediction model to achieve the intelligence of sentencing prediction. The effectiveness of the sentencing prediction model is examined by comparing the XGBoost model with different algorithms (Random Forest, CBDT, CNN). The practical application of intelligent decision support systems was summarized, highlighting the positive and negative effects. The results show that the overall responsiveness performance of the intelligent decision support system’s magisterial document capture and retrieval is reliable, and the number of captured and retrieved magisterial documents rises as the capture time increases. In XGBoost’s sentencing prediction, nine overlapping parts of the ten keywords were extracted for sentence and fine. In contrast, the keyword similarities are all higher than 0.5, and the difference between the predicted and real sentence values and fine is small. The intelligent decision support system has resulted in a gradual decrease in the number of court cases and an improvement in efficiency. The re-sentencing and retrial initiation rate decreased by over 20% from 2019 to 2023.

Analysis of directions for application of artificial intelligence systems in analysis of the state of water resources

Analysis of directions for application of artificial intelligence systems in analysis of the state of water resources

The Application of Intelligent Downhole Monitoring and Control Systems in Oil and Gas Production

The Application of Intelligent Downhole Monitoring and Control Systems in Oil and Gas Production

A Comprehensive Study on Self-Learning Methods and Implications to Autonomous Driving.

As artificial intelligence (AI) has already seen numerous successful applications, the upcoming challenge lies in how to realize artificial general intelligence (AGI). Self-learning algorithms can autonomously acquire knowledge and adapt to new, demanding applications, recognized as one of the most effective techniques to overcome this challenge. Although many related studies have been conducted, there is still no comprehensive and systematic review available, nor well-founded recommendations for the application of autonomous intelligent systems, especially autonomous driving. As a result, this article comprehensively analyzes and classifies self-learning algorithms into three categories: broad self-learning, narrow self-learning, and limited self-learning. These categories are used to describe the popular usage, the most promising techniques, and the current status of hybridization with self-supervised learning. Then, the narrow self-learning is divided into three parts based on the self-learning realization path: sample self-learning, model self-learning, and self-learning architecture. For each method, this article discusses in detail its self-learning capacity, challenges, and applications to autonomous driving. Finally, the future research directions of self-learning algorithms are pointed out. It is expected that this study has the potential to eventually contribute to revolutionizing autonomous driving technology.

Design and Practical Application of a Cost Effective Intelligent Female Surveillance System Using GPS, GSM, and Arduino Technology

This paper suggests a cost effective, portable and intelligent surveillance system for women that they can utilize in risky or emergency situations. In this design, an Arduino Nano microcontroller, a GPS module, and a GSM module are the main parts used. Whenever an emergency arises, the user can instantly send an emergency message to a preset phone number along with their current location. The emergency activation button is in a handy place on the gadget, which is tiny enough to carry in a pocket or purse. This device will improve women's protection and security, particularly in places with high crime rates or poor public safety.

Responsible and ethical application of artificial intelligence systems in healthcare through a case study in diagnostics and personalized medicine

Responsible and ethical application of artificial intelligence systems in healthcare through a case study in diagnostics and personalized medicine

Design and Application of Intelligent Library Intelligence Authentication System Based on Information Entropy Early Warning Models

Abstract Identifying the authenticity of library intelligence has consistently posed a significant challenge in intelligence management. This paper aims to optimize the D-S evidence theory to address the issues of uncertainty, imprecision, and high conflict in library intelligence evidence fusion. To achieve this, DSmT is employed to extend the D-S evidence theory by eliminating the process of assigning conflicting information with normalization coefficients. Then, through the fuzzy information pseudo-feature analysis method, the library intelligent intelligence information entropy feature quantity is extracted, and semantic feature matching is used to construct the library intelligent intelligence true and false information recognition system. Finally, the recognition performance of the system is examined using a dataset to analyze the intelligence authenticity recognition of mis-spliced bacterial colony genomic data from a biological experiment that has been entered into the library intelligence database. Finally, it was found that the average recognition rate of this paper's system in the four classical datasets is 96.57%, which is higher than the 89.61% and 90.02% of the two evidence fusion classification schemes. The results of this paper's algorithm for high-conflict evidence are 0.9506, 0.0558, and 0.0097, reflecting the accuracy of the evidence support results. Finally, 35 colony genome splicing error intelligence were identified, of which 32 were genuine errors, with a precision rate of 91% and a recall rate of 94%. The library intelligence authenticity recognition system designed in this paper has excellent performance and provides an effective path and usable algorithmic model for library intelligence authentication.

History of Technological Evolution in the Brazilian Judiciary System and the Application of Artificial Intelligence

Artificial Intelligence systems have been increasingly developing, demonstrating new forms of implementation and utilization, being employed in many sectors. In this regard, aiming to keep up with social development and enhance the development of procedural acts, the Brazilian Judiciary System has been seeking to implement new forms of technology over the years. Although gradually, an evolution can be observed in the sector, such as options that circumvent the use of physical documents and a departure from conducting all acts in person. This has led to the implementation and development of Artificial Intelligence systems within the judiciary, aiming to further improve the Brazilian judicial system. Therefore, this present work seeks to provide a historical overview of the advancements that have occurred in the Brazilian Judiciary System regarding its technological evolution, describing the initial modifications as well as the current applications of Artificial Intelligence. Additionally, it presents their objectives and capabilities. Thus, in conclusion, this paper demonstrates that the progress made over the years is immeasurable, and the application of Artificial Intelligence systems in the Brazilian Judiciary System is already becoming consolidated, with the potential for even greater growth in the coming years.

Speech recognition enhancement based on wireless network sensors application in interactive intelligent teaching system

The speech function used in the multi-dimensional speech recognition model based on MTL and RNN is the commonly used MFCC function, and in feature extraction, after various filtering and conversion, deleting part of the speech information is a requirement for 3D audio recognition. Use multidimensional information as much as possible. Based on this, this article not only brings the development of convolutional neural network intelligent teaching, but also proposes a new education model. Heuristic education like flipped classroom is still the content of education research in recent years, and it is important to the current education form in China. It is mainly based on the traditional lecture mode or the classroom form. This article focuses on undergraduate education. It is designed in the classroom based on the video data of the undergraduate interactive activities and the interactive system. It has important research significance and practicality. At the same time, the interactive content of the traditional teaching method is used to perform voice recognition, and the recognition effect of the main body of the interactive system is further improved through the voice information. The spatial perspective is used to divide the lens perspective into seminars and experimental forms, and the pixel change value of each frame provides a specific reference for it to determine the reflection of student interaction activities and the evaluation of student seminars. This article introduces the implementation process of interactive content and interactive activities of the teaching system in the classroom, introduces the speech recognition framework of the MARS Chinese teaching system, uses the model principle, and compares the general speech data set test with the actual ARST model audio. The results show that, MAS model performance is more advantageous.

Design and Implementation of Smart Teaching for Computer Courses in Colleges and Universities Enabled by Artificial Intelligence Technology

Abstract In this study, an intelligent decision support system for education was successfully constructed by integrating data mining techniques, evaluation similarity matrix and novel braided net clustering method. Based on the evaluation similarity matrix, this system brings together decision-making members with similar views through clustering analysis. It calculates these categorized groups’ preferences, consistency indexes, and decision values to derive the optimal solution. The research in this paper empirically validates the effectiveness of the intelligent decision support system against the background of actual teaching scenarios and with all students in their classes as the research subjects. The validation results show that in the Powerpoint Practical and PS Practical tests, the average scores of the students in the experimental class reached 87.1 and 86.2, respectively, and this score is significantly higher than that of the control class. In addition, in the Analysis of the four dimensions of pre-course learning behavior (including interest in learning, attitude toward learning, etc.), the mean values of the experimental class (4.46, 3.99, 3.89, 4.18) were also significantly higher than those of the control class (3.2, 2.73, 2.94, 2.89). The application of the Intelligent Decision Support System increased students’ learning interest and effectively improved their performance in both machine and written tests. The main effect of its teaching method is significant with an F-value of 18.029 and a P-value of less than 0.001. The results of this study confirm the practical application of intelligent decision support systems in teaching and learning, and provide a new methodology and perspective for computer-intelligent teaching.

Research on the method of fine-tuning teaching quality improvement in higher education under digital empowerment

Abstract With the rapid development of information technology, digital technology is also continuously applied to the teaching of higher education, and colleges and universities more and more emphasize the application of intelligent teaching guidance systems. A feature-weighted Bayesian algorithm is constructed in this study by assigning different weights to each attribute depending on its influence on the Bayesian classification results. On this basis, combined with the error-reversing BP neural network algorithm, it realizes refined intelligent instruction and develops an intelligent instruction system for higher education based on the ternary model. The transaction success rate reaches 98% when the number of concurrent users is below 4000, and the transaction success rate is 90% at 8000, and the system has good stability. The average classification accuracy of FWNB algorithm in this paper is 84.95%, which is larger than SWNB and HCWNB, and the average classification time is 3.17s, which is smaller than SWNB and HCWNB. The FWNB classifier achieves high classification accuracy at a low computational cost. The system in this paper can better mobilize learners’ enthusiasm, drive learners to study diligently and inspire learners to improve their learning ability, which leads to improved teaching quality.

Application and Practice of Intelligent Control System in Microcontroller Experiment Courses

Application and Practice of Intelligent Control System in Microcontroller Experiment Courses

ВНЕДРЕНИЕ ИНТЕЛЛЕКТУАЛЬНЫХ СИСТЕМ УПРАВЛЕНИЯ ДЛЯ АВТОМАТИЗИРОВАННЫХ ПОДСТАНЦИЙ

The article discusses the possibilities of implementing intelligent control systems at automated substations. The key advantages of such systems are emphasized, including increased reliability, resource optimization, and real-time decision support. Examples of successful application of intelligent systems are given, prospects for their further development are analyzed, and challenges associated with their integration into the existing infrastructure are considered.

Intelligent education management system design for universities based on MTCNN face recognition algorithm

Abstract This paper first constructs an intelligent education management system for universities according to their needs and explains its logical and technical architecture. Secondly, a multi-task convolutional neural network with MTCNN is used to detect faces, and different loss functions are selected to ensure recognition accuracy. Finally, the effectiveness of the application of intelligent education management systems in universities is verified through performance tests. The results show that the time consumed for face recognition detection using MTCNN is 524ms, and the response time of each function of the system does not exceed 500ms when the number of concurrent users is less than 500, which indicates that the intelligent education management system based on MTCNN face recognition algorithm has a good response speed and meets the requirements of intelligent education management in colleges and universities.