【正文】 cture of the PROTECTOR system Safety of mines and prevention of accidents is an issue of great importance in mine management. In order to be able to make appropriate and timely decision in this delicate matter the management needs to be adequately and accurately informed about the mine safety state on a daily basis. This information is, naturally, only part of the information required by mine manage ment. Information systems offer the tools and techniques for handling all the information flows in plex system such as mines. To that end, a Technological Information System (TIS) has been developed, which can be tailored to suit requirements of any mine in Serbia. It integrates the following modules: Human Resources, Maintenance, Mine Safety, Mine Planning and Produc tion, Management Information Decision Support System and Technical Data, and delivers critical internal and external information needed to support mining business. TIS ponents are integrated and operate with a unique database, and PROTECTOR, the hybrid system presented in this paper is part of the Mine Safety TIS module named MISS (Mine Safety Information System). The Unified Modeling Language (UML) diagram in Fig. 2 represents the structure of TIS and the place of MISS within TIS, as well as the structure of MISS and the place of the hybrid system Protector within MISS. UML, as a standard language for visualization, specification, constructing and documenting of data on software was adopted for the software development analysis phase. MISS module as a part of TIS contains several ponents such as: Health Care, Injuries and Professional Diseases, Personnel Safety Revises, Safety Reports. Each of these ponents has ponents of its own, as shown by the PROTECTOR system example. PROTECTOR prises several coupled software ponents, such as VB (Visual Basic) Application, Expert system, Neuro Application (Fig .2) (Lilic180。 Bent and Passmore, 1986。 外文資料原文 An intelligent hybrid system for surface coal mine safety analysis a b s t r a c t ： Analysis of safety in surface coal mines represents a very plex process. Published studies on mine safety analysis are usually based on research related to accidents statistics and hazard identification with risk assessment within the mining industry. Discussion in this paper is focused on the application of AI methods in the analysis of safety in mining environment. Complexity of the subject matter requires a high level of expert knowledge and great experience. The solution was found in the creation of a hybrid system PROTECTOR, whose knowledge base represents a formalization of the expert knowledge in the mine safety field. The main goal of the system is the estimation of mining environment as one of the significant ponents of general safety state in a mine. This global goal is subdivided into a hierarchical structure of subgoals where each subgoal can be viewed as the estimation of a set of parameters (gas, dust, climate, noise, vibration, illumination, geotechnical hazard) which determine the general mine safety state and category of hazard in mining environment. Both the hybrid nature of the system and the possibilities it offers are illustrated through a case study using field data related to an existing Serbian surface coal mine. 1. Introduction One of the most important and also most plex problems encountered in surface coal mines is safety analysis. An appro priate and reliable solution for this problem is vital for the working process in mines with surface exploitation. Published studies on mine safety analysis are usually based on research related to accidents statistics (Kecojevic and Radomsky, 2021。 Karra, 2021。 Marovelli, 1981). Several studies have been conducted on hazard identification and risk assessment (South African Mining Industry, 2021。 et al., 2021a, b). The system connects numerical methods with AI methods, thus introducing heuristics and forming a knowledge base with knowledge obtained from engineering practice. Fig. 2. Component viewoftechnologicalinformationsystem. In the proposed system, the ponent VB Application keeps records of mining environment characteristic, runs analysis and presents a result of the expert system analysis. The second ponent is a diagnostic expert system, which analyses the obtained results according to a series of criteria (gas, dust, climate, noise, vibration, illumination and geotechnical hazard). As a result of expert analysis, an estimation of validity and effectiveness of the mining environment state is obtained, followed by suggestions for its improvement. The architecture of the system and the software environment in which the system was developed provide for a dynamic munication between differ ent segments of the system and thus for unlimited possibilities of testing different modifications of the system and obtaining a final solution which satisfies all of the established criteria. Neuro application manages training of neural works for determination of permitted exposure time on specific vibration level. The neural work was trained through NeuroShell (Samarasinghe, 2021。 et al., 2021) with data obtained from diagrams for determination of permitted exposure time on specific vibration level in dependence of frequency and acceleration. PROTECTOR contains the ‘‘standard’’ elements of an expert system: the knowledge base, an inference engine, the user interface and a working memory, but also a module for the interface with routines for relevant parameters determination, the Visual Basic routines themselves, and a database used by these routines (Fig. 3). Fig. 3. Architecture of PROTECTOR expert system ponent. The main purpose of the user interface is to provide means for a successful dialogue, . an exchange of information between the user and the system. It is the user interface that