【正文】 ineering practice with the help of appropriate software products. Software products in mine safety need expert knowledge and experience to be fully exploited. This knowledge consists of rules and heuristics experts use when they apply numerical methods, and Artificial Intelligence offers formalisms and mechanisms for its incorporation in software systems (Russell and Norvig, 2021). Formalization of knowledge representation and development of mechanisms for using this knowledge are among methods and tools developed by AI for solving plex problems (Giarratano and Riley, 2021). However, the plexity of some problems outgrows the potentials of single methods. A possible solution is to bine two or more AI methods into a hybrid intelligent system (Goonatilake and Khebbal, 1995). This approach has been adopted in the case of PROTECTOR, a hybrid system for the analysis and estimation of safety in mining environment, devel oped at the Faculty of Mining and Geology of the University of Belgrade. PROTECTOR was developed by bining neural works and expert system technology. While the mining environment estimation methodology is implemented through an expert system, some of the related estimation parameters are determined by neural works. Discussion in this paper is focused on the application of bined AI methods in the analysis of safety in mining environment. A full understanding of the process and use of all collected data require the involvement of an experienced specialist in the mine safety field. The solution was found in the creation of PROTECTOR, whose knowledge base represents a formalization of the expert knowledge in the mine safety field. Section 2 of this paper outlines the global problemsolving strategy through a hierarchical deposition of the main goal, the evaluation of the mining environment, and the formalization of this strategy by means of a modified objectoriented analysis (OOA) model. The system structure and the main architectural ponents of the PROTECTOR system are described in Section 3. The implementation of the system in the KAPPAPC expert systems shell is discussed in Section 4. Section 5 presents a case study, followed by a conclusion in the last section. 2. A formalization of mining environment evaluation problemsolving Analysis of safety in coal mines represents a very plex process based on estimation of numerous and interdependent parameters that are classified into several basic criteria for estimation of mining environment. These criteria are related to the following conditions: gas, dust, climate, noise, vibration, illumination and geotechnical hazard (highwall stability and waste stability). In discussing occupational risks in the mining industry, it is mon practice to identify health and safety hazards separately. Some of these environmental stresses may interact to produce a greater overall effect. In bination or alone, if environmental stresses exceed human tolerance levels for prolonged periods of time, feelings of disfort will arise, alertness will decrease, accidents will occur, and performance and productivity will drop. Mining is among the more traditional and conservative engineering disciplines. Although various assessment techniques and numerical methods are available, the analysis of safety in surface coal mines relies mostly on heuristics formulated by mine safety experts. This was precisely the motivation for developing of PROTECTOR as a hybrid system, with its expert system ponent in its core. The system architecture draws upon the experience gained by successful implementation of hybrid systems in different fields, but represents a novel approach when mining is concerned. The novelty of the approach to mine safety was further reinforced by the development of an evaluation strategy. The main goal of the system is the estimation of mining environment as one of the significant ponents of general safety state in mine. This global goal can be subdivided into a hierarchical structure of subgoals where each of these subgoals can be viewed as the estimation of a set of parameters (gas, dust, climate, noise, vibration, illumination and geotechnical hazard) which determine the general mine safety state and category of hazard in mining environment. During this process, the importance, . significance of each particular parameter must be taken into account. The hierarchical deposition of the main goal into subgoals, representing the problemsolving strategy, makes it easier to cope with the plexities and to coordinate the use of the knowledge incorporated in the system. The strategy for evaluation of the safety in mining environ ment is formally represented using a modification of the CoadYourdon objectoriented analysis (OOA) model (Coad and Yourdon, 1991). In the standard model every real world entity is represented by a class (object) consisting of its name, attributes and methods pertaining to the procedures related to the object. However, in order to incorporate declarative knowledge, we have resorted to a modification of this model by including a new (fourth) element, featuring the production (IFTHEN) rules related to an object in the model. Thus both the procedural and declara tive knowledge related to a class object could be represented. Such a modified OOA model was then used for the representation of the mining environment evaluation strategy as well as other objects in the system and their mutual relationships (Fig. 1). Fig. 1. Modified OOAmodeloftheminingenvironmentevaluation The inheritance relations between hierarchically connected objects representing elements of the strategy are given by full lines, while the exchange of messages between classes is represented with dotted lines. The model was the basis for the implementation of the system in an objectoriented expert system shell. 3. Archite