Effective Approach to Elevate the Intelligence of Management Decision System

Based on the sticking point of the low intelligence of the existing management decision system,this paper puts forward the idea of enriching and refining the knowledge of the system and endowing it with the ability to learn by means of adopting three types of heterogeneous knowledge representation and knowledge management measures.At length,this paper outlines the basic framework of an intelligence system for the sake of management decision problem.

Application of oblique photogrammetry technique in geological hazard identification and decision management

With the continuous development of the oblique photography technique, it has been used more and more widely in the field of geological disasters. It can quickly obtain the three-dimensional(3D) real scene model of dangerous mountainous areas under the premise of ensuring the safety of personnel while restoring the real geographic information as much as possible. However, geological disaster areas are often accompanied by many adverse factors such as cliffs and dense vegetation. Based on this, the paper introduced the flight line design of oblique photogrammetry, analyzed the multi-platform data fusion processing, studied the multi-period data dynamic evaluation technology and proposed the application methods of data acquisition, early warning, disaster assessment and decision management suitable for geological disaster identification through the analysis of actual cases, which will help geologists to plan and control geological work more scientifically and rationally, improve work efficiency and reduce the potential personnel safety hazards in the process of geological survey, to offer technical support to the application of oblique photogrammetry in geological disaster identification and decision making and provide the scientific basis for personal and property safety protection and later-stage geological disaster management in disaster areas.

Effects of lag time in forest restoration and management

The increased speed of global change and associated high severity disturbances,in conjunction with the increasing suite of societal expectations on forests,suggest that the timeliness of interventions to encourage the adaptive capacity of ecosystems and to reduce negative impacts in regards to provision of ecosystem services is increasingly relevant.To address this issue,we expand the concept of lag time as used in ecological discussions into a forest management context.In this context,lag times have earlier starting and later ending points and can be separated into different components.These components include the delay till detection,decision making,and implementation,followed by ecological lag time and the time till ecosystem services are provided at acceptable levels.The first three components are influenced by the availability of information,the lack of which can extend lag times.Also,the lengths of components are not simply additive but they interact.For example,treatment preparation due to a quicker detection can lead to shorter decision and implementation lag times.We highlight the benefits of addressing the various components of lag time in forestry operations.Especially when considering adaptive capacity in times of global change,our analysis suggests that all aspects of the forestry sector are challenged to consider how to optimize lag times.Last,we propose that such issues need to be considered with any management action and are especially relevant in discussions whether the best strategy after disturbances or in the light of global change is to adopt a passive approach and let natural ecosystem processes play out on their own or whether active management is better suited to ensure a more rapid and fitting ecosystem response to facilitate the continued provision of ecosystem services.

Research on Decision Support System (DSS) of Atmospheric Environment Management in Anhui Province Based on Air Quality Forecasting

With the atmospheric stereoscopic monitoring, air quality forecasting and decision of environment management as the main line, and comprehensive management system as the guidance, five platforms including infrastructure, technological support, monitoring and early monitoring, decision support and information services were established. These platforms have 15 subsystems, including stereoscopic monitoring network, visual business consultation, high-performance computing environment, comprehensive management of atmospheric data, emission inventories of pollu-tion sources, evaluation tools of atmospheric models, monitoring and management of air pollution, forecasting and early warning of air quality, diag-nostic analysis of atmospheric environment, tracking of air pollution sources, emergency management of air pollution, conformity management of air quality, comprehensive display of information, releasing of information to external networks, and releasing of information by mobile networks. The decision support system （DSS） of atmospheric environment management could realize an integration business system of 11 air quality forecast - heavy pollution weather warning - diagnosis of pollution causes （dynamic analysis of pollution sources） -air quality conformity planning （air pollu-tion emergency management） -evaluation of forecasting and warning results （evaluation pf management measures） -air quality forecasting＂ and provide the technical support for the prevention and control of atmosphere pollution in Anhui province.

Flood Forecasting GIS Water-Flow Visualization Enhancement (WaVE): A Case Study

Riverine flood event situation awareness and emergency management decision support systems require accurate and scalable geoanalytic data at the local level. This paper introduces the Water-flow Visualization Enhancement (WaVE), a new framework and toolset that integrates enhanced geospatial analytics visualization (common operating picture) and decision support modular tools. WaVE enables users to: 1) dynamically generate on-the-fly, highly granular and interactive geovisual real-time and predictive flood maps that can be scaled down to show discharge, inundation, water velocity, and ancillary geomorphology and hydrology data from the national level to regional and local level;2) integrate data and model analysis results from multiple sources;3) utilize machine learning correlation indexing to interpolate streamflow proxy estimates for non-functioning streamgages and extrapolate discharge estimates for ungaged streams;and 4) have time-scaled drill-down visualization of real-time and forecasted flood events. Four case studies were conducted to test and validate WaVE under diverse conditions at national, regional and local levels. Results from these case studies highlight some of WaVE’s inherent strengths, limitations, and the need for further development. WaVE has the potential for being utilized on a wider basis at the local level as data become available and models are validated for converting satellite images and data records from remote sensing technologies into accurate streamflow estimates and higher resolution digital elevation models.

The Design of Intelligent Corporate E-commerce System

The paper shows how to design and implement an inte ll igent e-commerce system for medium or small enterprises. The corporate intranet is connected with Internet, which constitutes the hardware of the system. The s ystem adopts modern voice-identification technology for user authentication to enable secure access to key databases and thus enhance the security of system da tabases. The software system consists of four modules: 1. Corporate website and advertisement information system, intending for updatin g online advertisement, collecting and analyzing market research information. 2. Employee technology training and assessment system, including a variety of co urses containing technology, technique and management and so on. Login the training system, employees are able to study courses of technology or technique or others. The training system adopts modern multimedia E-Learning te chnology and in fact it is an innovative education method, which includes self- study, tutorship and lecture. It is able to help employees enjoy their learning. Employees can take simulative exams, and managers can test employees onlin e periodically. 3. Corporate decision-making management system, calculating and analyzing the o peration, predicting future development, facilitating communication between mana gers and employees. It provides valuable foundation for decisions, which enables managers to make strategic decisions and scientific management. 4. E-commerce online transaction system, which facilitates material purchase an d product sale. By using intelligent e-commerce system, corporations will enhance the employee’ s skills and management level, reduce production cost, promote product sale , and thus strengthen corporation’s market competitiveness effectively.

Situation and Development of SME e-commerce

Economic globalization is the core of information technology, information technology is the core of e-commerce. E-commerce is as an important part of inlbrnaation technology in recent years when China has been booming. For a large number of SMEs, human resources, capital, technology and information are in a relatively weak position, in addition, in recent years, changes in the external environment in which small and medium enterprises are also reflected in： international trade friction increase, RMB such as the increasing appreciation of the exchange rate increase, it raises the cost of export products. Under the new situation, how to find space for development, how to implement e-commerce strategy, clutches the huge growth opportunities given the times, to keep pace with the times, in an invincible position in the competitive market environment, many small and medium enterprises become China＇ s urgent problems.

Comprehensive Dynamics of Banking: A Systemic Approach Incorporating Lending, Investment, and Capital Variables

The research topic related to the analysis of banking activity is relevant since the banking sector is complex and dynamic and requires constant monitoring and analysis to make informed decisions. Using a mathematical model of system dynamics to analyse banking activities can help banks make better decisions, manage risk, ensure the stability and efficiency of operations, and adapt to changing conditions. The purpose of the study is to determine the influence of various factors, in particular economic activity, on the final profit of the bank. Among the methods used, the analytical method, the functional method, the system analysis method, the deduction method, the synthesis method, and the comparison method were applied. In the course of this study, an extensive analytical review of banking activities was carried out using a system dynamics model, taking into account the requirements of the International Financial Reporting Standards(IFRS 9). The study included various scenario analyses to explore the impact of changes in economic conditions on the bank's loan portfolio,risk level, and profitability. Both economic growth scenarios and recession scenarios were considered in order to more fully assess their impact on the financial condition of the bank. A forecast and analysis of the risks associated with lending, investments, and other bank operations was carried out. The practical significance lies in the application of the results obtained to address issues related to banking in order to increase the efficiency of this process and achieve a new level of development.

Cyber risk at the edge:current and future trends on cyber risk analytics and artificial intelligence in the industrial internet of things and industry 4.0 supply chains

Digital technologies have changed the way supply chain operations are structured.In this article,we conduct systematic syntheses of literature on the impact of new technologies on supply chains and the related cyber risks.A taxonomic/cladistic approach is used for the evaluations of progress in the area of supply chain integration in the Industrial Internet of Things and Industry 4.0,with a specific focus on the mitigation of cyber risks.An analytical framework is presented,based on a critical assessment with respect to issues related to new types of cyber risk and the integration of supply chains with new technologies.This paper identifies a dynamic and self-adapting supply chain system supported with Artificial Intelligence and Machine Learning(AI/ML)and real-time intelligence for predictive cyber risk analytics.The system is integrated into a cognition engine that enables predictive cyber risk analytics with real-time intelligence from IoT networks at the edge.This enhances capacities and assist in the creation of a comprehensive understanding of the opportunities and threats that arise when edge computing nodes are deployed,and when AI/ML technologies are migrated to the periphery of IoT networks.

Cyber risk at the edge:current and future trends on cyber risk analytics and artificial intelligence in the industrial internet of things and industry 4.0 supply chains

Digital technologies have changed the way supply chain operations are structured.In this article,we conduct systematic syntheses of literature on the impact of new technologies on supply chains and the related cyber risks.A taxonomic/cladistic approach is used for the evaluations of progress in the area of supply chain integration in the Industrial Internet of Things and Industry 4.0,with a specific focus on the mitigation of cyber risks.An analytical framework is presented,based on a critical assessment with respect to issues related to new types of cyber risk and the integration of supply chains with new technologies.This paper identifies a dynamic and self-adapting supply chain system supported with Artificial Intelligence and Machine Learning(AI/ML)and real-time intelligence for predictive cyber risk analytics.The system is integrated into a cognition engine that enables predictive cyber risk analytics with real-time intelligence from IoT networks at the edge.This enhances capacities and assist in the creation of a comprehensive understanding of the opportunities and threats that arise when edge computing nodes are deployed,and when AI/ML technologies are migrated to the periphery of IoT networks.