Construction of Intelligent Recommendation Retrieval Model of FuJian Intangible Cultural Heritage Digital Archives Resources

In order to improve the consistency between the recommended retrieval results and user needs,improve the recommendation efficiency,and reduce the average absolute deviation of resource retrieval,a design method of intelligent recommendation retrieval model for Fujian intangible cultural heritage digital archive resources based on knowledge atlas is proposed.The TG-LDA(Tag-granularity LDA)model is proposed on the basis of the standard LDA(Linear Discriminant Analysis)model.The model is used to mine archive resource topics.The Pearson correlation coefficient is used to measure the relevance between topics.Based on the measurement results,the FastText deep learning model is used to achieve archive resource classification.According to the classification results,TF-IDF(term frequency–inverse document frequency)algorithm is used to calculate the weight of resource retrieval keywords to achieve resource retrieval,and a recommendation model of intangible cultural heritage digital archives resources is built through the knowledge map to achieve comprehensive and personalized recommendation of resources.The experimental results show that the recommendation and retrieval results of the proposed method are more in line with users’needs,can provide users with personalized digital archive resources,and the average absolute deviation of resource retrieval is low,the recommendation efficiency is high,and the utilization effect of archive resources is effectively improved.

Intelligent Recommendation and Matching Method for Agricultural Knowledge Based on Context-Aware Models

The personalized recommendation of the cloud platform for agricultural knowledge and agricultural intelligent service is one of the core technologies for the development of smart agriculture.Revealing the implicit laws and dynamic characteristics of agricultural knowledge demand is a key problem to be solved urgently.In order to enhance the matching ability of knowledge recommendation and service in human-computer interaction of cloud platform,the mechanism of agricultural knowledge intelligent recommendation service integrated with context-aware model was analyzed.By combining context data acquisition,data analysis and matching,and personalized knowledge recommendation,a framework for agricultural knowledge recommendation service is constructed to improve the ability to extract multidimensional information features and predict sequence data.Using the cloud platform for agricultural knowledge and agricultural intelligent service,this research aims to deliver interesting video service content to users in order to solve key problems faced by farmers,including planting technology,disease control,expert advice,etc.Then the knowledge needs of different users can be met and user satisfaction can be improved.

Video Recommendation System Using Machine-Learning Techniques

In the realm of contemporary artificial intelligence,machine learning enables automation,allowing systems to naturally acquire and enhance their capabilities through learning.In this cycle,Video recommendation is finished by utilizing machine learning strategies.A suggestion framework is an interaction of data sifting framework,which is utilized to foresee the“rating”or“inclination”given by the different clients.The expectation depends on past evaluations,history,interest,IMDB rating,and so on.This can be carried out by utilizing collective and substance-based separating approaches which utilize the data given by the different clients,examine them,and afterward suggest the video that suits the client at that specific time.The required datasets for the video are taken from Grouplens.This recommender framework is executed by utilizing Python Programming Language.For building this video recommender framework,two calculations are utilized,for example,K-implies Clustering and KNN grouping.K-implies is one of the unaided AI calculations and the fundamental goal is to bunch comparable sort of information focuses together and discover the examples.For that K-implies searches for a steady‘k'of bunches in a dataset.A group is an assortment of information focuses collected due to specific similitudes.K-Nearest Neighbor is an administered learning calculation utilized for characterization,with the given information;KNN can group new information by examination of the‘k'number of the closest information focuses.The last qualities acquired are through bunching qualities and root mean squared mistake,by using this algorithm we can recommend videos more appropriately based on user previous records and ratings.

Application of Electronic Information Engineering in Hospital Management

To further enhance the overall service quality of China’s hospitals and improve the trust of the majority of patients in hospitals,this paper takes intelligent hospital management as the object of study,analyzes the importance of electronic information engineering technology applied in hospital management,and discusses the specific application methods of electronic information engineering in hospital management.This aims the existing problems in the current hospital management,such as insufficient degree of informatization,data sharing difficulties,lack of professionals,etc.Corresponding improvement measures are proposed,including strengthening the construction of informatization,promoting data sharing,and cultivating professionals.It is hoped that this study will enable the majority of hospital managers to make better use of electronic information engineering technology to effectively solve the current problems faced by hospitals and to continuously improve the comprehensive competitiveness of China’s hospitals.

基于ArcGIS Engine的城市绿地生态网络智能规划系统研发与实证

针对现有城市绿地生态网络构建方法复杂多样、常用软件功能单一、规划支撑效果有限等问题,研发了城市绿地生态网络智能规划系统。将保护生物多样性、提升功能连接度作为城市尺度绿地生态网络构建的核心目标,统筹其他生态与社会服务功能,梳理和综合图论、生境质量评价、最小累积阻力模型和电路理论等生态网络模拟和分析方法,基于NET平台,采用ArcGIS Engine、C#、Python等技术,通过GIS二次开发方式实现系统各项功能,并以上海市闵行区为对象进行了实证分析。结果表明,系统可自动执行生态源地筛选、综合阻力面构建、生态廊道路径提取、生态廊道宽度确定、生态网络效能评价等技术环节,一键生成城市绿地生态网络布局结构,并实现不同情景的对比分析,为规划实践提供多情景、可视化的辅助决策。

Hyperspectral Intelligent Monitoring System of Major Soil Nutrients Based on ArcGIS Engine

Based on the object-oriented concept,the hyperspectral intelligent monitoring system of major soil nutrients was designed and developed by using C# and ArcGIS Engine in combination with Microsoft SQL Server.The system mainly includes the following functions：file operation,basic map operation,spectral preprocessing,model management,nutrient content quick calculation,spatial distribution analysis,user management and so on.This system can accomplish the input and preprocessing of soil hyperspectra,and calculate the content of major nutrients,such as soil organic matter,nitrogen,phosphorus as well as potassium quickly and intelligently based on hyperspectral data.Thereby,the soil nutrients regional distribution in the research area can be analyzed by using the principle of geostatistics.This study can not only promote the practicability of soil quantitative remote sensing,but also provide references for the decision-making of agricultural fertilizing.

Intelligent outdoor video advertisement recommendation system based on analysis of audiences' characteristics

An integrated implementation framework of an intelligent recommendation system for outdoor video advertising is proposed, which is based on the analysis of audiences＇ characteristics. Firstly, the images of the scene and the people who view the video advertisements are captured by the net- work camera deployed on the video advertising terminal side. Then audiences＇ characteristics can be obtained by applying computer vision technologies ： face detection, face tracking, gender recogni- tion and age estimation. Finally, an intelligent recommendation algorithm is designed to decide the most fitting video ads for each terminal according to multi-dimensional statistical information of its reover, a novel face detection method and a new face tracking method have been proposed to meet the practical requirements of the system, of which the average Fl-score is O. 988 and 0. 951 respec- tively.

Intelligent Control Scheme of Engineering Machinery of Cluster Hybrid System

In a hybrid system, the subsystems with discrete dynamics play a central role in a hybrid system. In the course of engineering machinery of cluster construction, the discrete control law is hard to obtain because the construction environment is complex and there exist many affecting factors. In this paper, hierarchically intelligent control, expert control and fuzzy control are introduced into the discrete subsystems of engineering machinery of cluster hybrid system, so as to rebuild the hybrid system and make the discrete control law easily and effectively obtained. The structures, reasoning mechanism and arithmetic of intelligent control are replanted to discrete dynamic, conti- nuous process and the interface of the hybrid system. The structures of three types of intelligent hybrid system are presented and the human experiences summarized from engineering machinery of cluster are taken into account.

Intelligent Petroleum Engineering

Data-driven approaches and artificial intelligence(AI)algorithms are promising enough to be relied on even more than physics-based methods;their main feed is data which is the fundamental element of each phenomenon.These algorithms learn from data and unveil unseen patterns out of it The petroleum industry as a realm where huge volumes of data are generated every second is of great interest to this new technology.As the oil and gas industry is in the transition phase to oilfield digitization,there has been an increased drive to integrate data-driven modeling and machine learning(ML)algorithms in different petroleum engineering challenges.ML has been widely used in different areas of the industry.Many extensive studies have been devoted to exploring AI applicability in various disciplines of this industry;however,lack of two main features is noticeable.Most of the research is either not practical enough to be applicable in real-field challenges or limited to a specific problem and not generalizable.Attention must be given to data itself and the way it is classified and stored.Although there are sheer volumes of data coming from different disciplines,they reside in departmental silos and are not accessible by consumers.In order to derive as much insight as possible out of data,the data needs to be stored in a centralized repository from where the data can be readily consumed by different applications.

The Application of Book Intelligent Recommendation Based on the Association Rule Mining of Clementine

The traditional library can’t provide the service of personalized recommendation for users. This paper used Clementine to solve this problem. Firstly, model of K-means clustering analyze the initial data to delete the redundant data. It can avoid scanning the database repeatedly and producing a large number of false rules. Secondly, the paper used clustering results to perform association rule mining. It can obtain valuable information and achieve the service of intelligent recommendation.

Materials Science-Technology and Intelligent Engineering

This paper analyses the peculiar acting mechanism of artificial neural network (ANN) tech, and explores the great immediate significence for the intelligent sci-tech (IST) to research and develop the nano-tech.

Research and Modelling on the E-commerce Consumer Behavior based on Intelligent Recommendation System and Machine Learning

In this paper, we conduct research on the E-commerce consumer behavior based on the intelligent recommendation system andmachine learning. Closely associated with consumer network information search of a problem is that the consumer’s information demand ascan be thought of consumer’s information demand is leading to trigger the power of consumer network information search behavior, whenconsumer is willing to buy goods, in a certain task under the infl uence of factors, environmental factors, individual factors, consumers and thetask object interaction to form the demand of consumer cognition. Under this basis, this paper proposes the new idea on the related issues thatwill solve the related challenges.

System Design and Implementation of Intelligent Fire Engine Path Planning based on SAT Algorithm

In this paper, in order to make intelligent fi re car complete autonomy path planning in simulation map. Proposed system design of intelligent fi re car path planning based on SAT. The system includes a planning module, a communication module, a control module. Control module via the communication module upload the initial state and the goal state to planning module. Planning module solve this planning solution,and then download planning solution to control module, control the movement of the car fi re. Experiments show this the system is tracking short time, higher planning effi ciency.

Application Strategy of Intelligent Technology in Electronic Engineering Automation Control

This paper proposes the application strategy of the intelligent technology in electronic engineering automation control. Artificial intelligence technology is about to realize the calculation of perception, reasoning and behavior study of it is different from most of the psychology, because it is more of an emphasis on the calculation, the artificial intelligence is also different from most of the computer science as because it is more of an emphasis on the perception, reasoning, and behavior, and future applications of artificial intelligence is beyond imagination. Regarding the multi-agent system target identification data fusion, the goal type is a proposition, each intelligent body gives through processing regarding the goal type judgment result is evidence, we discussed in detail of the essential applications on the item that will promote the further development.

Research on Innovation of Engineering Project Management Mode and Intelligent Management

In order to realize the standardization and normalization of environmental protection project management.This paper uses the literature method to study the current status of the existing project management mode,and points out the problems:lack of a sound project management system,insufficient information application of project management,and unclear decentralization in project management;on this basis,this paper proposes optimization strategies from the aspects of perfecting the engineering project management system,clarifying the allocation of project management authority,and strengthening the construction of engineering project management information.And put forward the future development trend of project engineering management,on the basis of two mainstream management modes of BOT(Build-Operate-Transfer)and EPC(Engineering Procurement Construction),build a standardized project management platform to achieve intelligent management.Realize intelligent management of engineering project management to achieve standardization and standardization,greatly improving the efficiency of project management.

Intelligent Vascularized 3D/4D/5D/6D‑Printed Tissue Scaffolds

Blood vessels are essential for nutrient and oxygen delivery and waste removal.Scaffold-repairing materials with functional vascular networks are widely used in bone tissue engineering.Additive manufacturing is a manufacturing technology that creates three-dimensional solids by stacking substances layer by layer,mainly including but not limited to 3D printing,but also 4D printing,5D printing and 6D printing.It can be effectively combined with vascularization to meet the needs of vascularized tissue scaffolds by precisely tuning the mechanical structure and biological properties of smart vascular scaffolds.Herein,the development of neovascularization to vascularization to bone tissue engineering is systematically discussed in terms of the importance of vascularization to the tissue.Additionally,the research progress and future prospects of vascularized 3D printed scaffold materials are highlighted and presented in four categories:functional vascularized 3D printed scaffolds,cell-based vascularized 3D printed scaffolds,vascularized 3D printed scaffolds loaded with specific carriers and bionic vascularized 3D printed scaffolds.Finally,a brief review of vascularized additive manufacturing-tissue scaffolds in related tissues such as the vascular tissue engineering,cardiovascular system,skeletal muscle,soft tissue and a discussion of the challenges and development efforts leading to significant advances in intelligent vascularized tissue regeneration is presented.

Analysis of Intelligent Construction Technology of Building Prefabricated Components Based on BIM

In this paper,the intelligent construction of prefabricated components is analyzed based on building information modeling(BIM).It includes an overview of BIM-based prefabricated components and intelligent construction,intelligent production lines in BIM-based intelligent construction systems,and analysis of the application of intelligent manufacturing in BIM-based prefabricated components.It was found that the determination of construction goals,the establishment of intelligent construction systems,and the application of intelligent construction systems are all areas that need to be emphasized in producing prefabricated building components through intelligent construction.It is hoped that this analysis can provide some reference for the application of intelligent construction and the improvement of the quality of prefabricated building components.

Explainable Rules and Heuristics in AI Algorithm Recommendation Approaches——A Systematic Literature Review and Mapping Study

The exponential use of artificial intelligence(AI)to solve and automated complex tasks has catapulted its popularity generating some challenges that need to be addressed.While AI is a powerfulmeans to discover interesting patterns and obtain predictive models,the use of these algorithms comes with a great responsibility,as an incomplete or unbalanced set of training data or an unproper interpretation of the models’outcomes could result in misleading conclusions that ultimately could become very dangerous.For these reasons,it is important to rely on expert knowledge when applying these methods.However,not every user can count on this specific expertise;non-AIexpert users could also benefit from applying these powerful algorithms to their domain problems,but they need basic guidelines to obtain themost out of AI models.The goal of this work is to present a systematic review of the literature to analyze studies whose outcomes are explainable rules and heuristics to select suitable AI algorithms given a set of input features.The systematic review follows the methodology proposed by Kitchenham and other authors in the field of software engineering.As a result,9 papers that tackle AI algorithmrecommendation through tangible and traceable rules and heuristics were collected.The reduced number of retrieved papers suggests a lack of reporting explicit rules and heuristics when testing the suitability and performance of AI algorithms.

人工智能在土木工程领域的应用研究现状及展望

作为新一代产业变革的核心驱动力,人工智能是全面提高土木工程领域数字化、自动化、信息化和智能化的重要方法。为全面了解人工智能在土木工程中的发展及应用,定性分析了人工智能的基本研究领域,定量分析了人工智能在土木工程设计、制造、养维护阶段的研究现状,利用CiteSpace可视化工具深入挖掘人工智能在土木工程中存在的问题、发展瓶颈和研究趋势,并给出相应的解决办法及研究思路。通过文献综述发现,土木工程领域已展开了大量人工智能研究,但各阶段智能化发展不均衡,实际应用也存在一定局限性,需深入探索神经网络、大数据、深度学习等智能技术在土木工程全生命周期的交叉融合,促进土木工程领域人工智能研究的协同发展。

Analyzing the Impact of Blockchain Models for Securing Intelligent Logistics through Unified Computational Techniques

Blockchain technology has revolutionized conventional trade.The success of blockchain can be attributed to its distributed ledger characteristic,which secures every record inside the ledger using cryptography rules,making it more reliable,secure,and tamper-proof.This is evident by the significant impact that the use of this technology has had on people connected to digital spaces in the present-day context.Furthermore,it has been proven that blockchain technology is evolving from new perspectives and that it provides an effective mechanism for the intelligent transportation system infrastructure.To realize the full potential of the accurate and efficacious use of blockchain in the transportation sector,it is essential to understand the most effective mechanisms of this technology and identify the most useful one.As a result,the present work offers a priority-based methodology that would be a useful reference for security experts in managing blockchain technology and its models.The study uses the hesitant fuzzy analytical hierarchy process for prioritizing the different blockchain models.Based on the findings of actual performance,alternative solution A1 which is Private Blockchain model has an extremely high level of security satisfaction.The accuracy of the results has been tested using the hesitant fuzzy technique for order of preference by similarity to the ideal solution procedure.The study also uses guidelines from security researchers working in this domain.