Synergetic knowledge bases

Modern knowledge bases must largely correspond to human thinking and the reality of the world. Synergetic knowledge bases create the possibility of joint use of both "hard" computing, which require the accuracy and unique-ness of the solution, and "soft" computing, allowing a given error and uncertainty for a specific problem. A methodolo-gy for creating synergetic systems for the representation of knowledge using artificial intelligence technologies is pro-posed. The methodology is based on knowledge base methods and can be used to develop design and management systems in industries. A model for representing linguistic variables is proposed. The method of creating fuzzy knowledge bases and the stages of the inference mechanism are considered. The fuzzy inference is described using the example of the Mamdani mechanism. A functional diagram of the creation of fuzzy inference systems based on a structured clear knowledge module is proposed. A method for creating knowledge bases for the implementation of neural network models is considered. An example of a knowledge base for training neural networks is given.

Modeling Study on Risk Identification in the Process of Anti-Crisis Enterprise Management

The study provides solutions for the scientific task related to the improvement of theoretical and development of methodological and applied principles, and the identification and evaluation of risks and threats as factors of anti-crisis management of the enterprises. Based on the developed concept of quantitative risk analysis, we constructed a fuzzy hierarchical model, which gives the possibility to get the estimates: risk factors; specific types of threats in the framework of a process; risk processes, identified in the anti-crisis management; and the integrative risk of anti-crisis management. Furthermore, the proposed model makes it possible to identify the threats that are the risks of the highest (catastrophe) layer. The fuzzy hierarchical model construction process includes the determination of linguistic variables, term-varieties, and universal sets for quantitative evaluation of figures and risks, the establishment of parameters of the membership functions for indicators and risks, the formation of fuzzy knowledge bases, the construction of a fuzzy hierarchical model in the MATLAB environment, the evaluation of adequacy of model based on the learning sample, the correction of a model, and the adoption of a resolution regarding its final variant. The use of the model in the anti-crisis enterprise management will provide the anti-crisis team with the possibility to give early warning of all negative factors, give their quantitative evaluation, and take them into account in the course of making managerial decisions.

Television Rating Control in the Multichannel Environment Using Trend Fuzzy Knowledge Bases and Monitoring Results †

The purpose of this study is to control the ratio of programs of different genres whenforming the broadcast grid in order to increase and maintain the rating of a channel. In themultichannel environment, television rating controls consist of selecting content, the ratings ofwhich are completely restored after advertising. The hybrid approach to rule set refinement basedon fuzzy relational calculus simplifies the process of expert recommendation systems construction.By analogy with the problem of the inverted pendulum control, the managerial actions aim to retainthe balance between the fuzzy demand and supply. The increase or decrease trends of the demandand supply are described by primary fuzzy relations. The rule-based solutions of fuzzy relationalequations connect significance measures of the primary fuzzy terms. Program set refinement bysolving fuzzy relational equations allows avoiding procedures of content-based selective filtering.The solution set generation corresponds to the granulation of television time, where each solutionrepresents the time slot and the granulated rating of the content. In automated media planning,generation of the weekly TV program in the form of the granular solution provides the decrease oftime needed for the programming of the channel broadcast grid.

Television Rating Control in the Multichannel Environment Using Trend Fuzzy Knowledge Bases and Monitoring Results

The purpose of the study is to control the ratio of programs of different genres when forming the broadcast grid in order to increase and maintain the rating of the channel. In the multichannel environment, television rating control consists of selecting such content, ratings of which are completely restored after advertising. A hybrid approach combining the benefits of semantic training and fuzzy relational equations in simplification of the expert recommendation systems construction is proposed. The problem of retaining the television rating can be attributed to the problems of fuzzy resources control. The increase or decrease trends of the demand and supply are described by primary fuzzy relations. The rule-based solutions of fuzzy relational equations connect significance measures of the primary fuzzy terms. Rules refinement by solving fuzzy relational equations allows avoiding labor-intensive procedures for the generation and selection of expert rules. The solution set generation corresponds to the granulation of the television time, where each solution represents the time slot and the granulated rating of the content. In automated media planning, generation of the weekly TV program in the form of the granular solutions provides the decrease of the time needed for the programming of the channel broadcast grid.

Intelligent Technologies in the Examination of Construction Structures

Categoiy of technical condition (normative, workable imited operational or emergency), which is determined by engineering inspection of buildings and structures, is the main criterion in making decisions about the degree of accident or the need to take measures to bring it to further use. The decisions taken depend on the objectivity and reliability of the information provided ty expertswhich sometimes cannot be interpreted as completely true or complete^ false. It seems advisable to strengthen and expand the professional capabilities of specialists who are engaged in the survey of construction sites through the use of expert systems on the basis of the mathematical apparatus of the theoiy of fuzzy sets and fuzzylogic. This makes it possible to take into account the scatter of individual opinions. Information from the subject area of technical diagnostics of buildings is formalized in terms of fuzzy sets with the use of membership functions created for both input and output control parameters. To implement the fuzzy logical inference, Mamdani's algorithm, modified and adapted to the given problem, was proposed. This technology allows to give a strict mathematical description of vague statements realizing an attempt to overcome alinguistic barrier between a person whose judgments and assessments are approximate and indistinct and a computer that can on^ perform clear instructions. A computer program has been developed that implements the method of identification of the category of technical condition of building structures on the basis of fuzzy knowledge bases.

A Model-Based Virtual Sensor for Condition Monitoring of Li-Ion Batteries in Cyber-Physical Vehicle Systems

A model-based virtual sensor for assessing the health of rechargeable batteries for cyber-physical vehicle systems (CPVSs) is presented that can exploit coarse data streamed from on-vehicle sensors of current, voltage, and temperature. First-principle-based models are combined with knowledge acquired from data in a semiphysical arrangement. The dynamic behaviour of the battery is embodied in the parametric definition of a set of differential equations, and fuzzy knowledge bases are embedded as nonlinear blocks in these equations, providing a human understandable reading of the State of Health of the CPVS that can be easily integrated in the fleet through-life management.