Abstract
The article shows the importance for the food industry automation control online quality raw material, finished products, identification of marriage. Based-WAN the ability to solve this problem using computer vision systems (CPS). The article presents the problems solved by the computer vision system. Brief description of the goals of computer vision in various applications. Considering Rena structure of market demand and computer vision systems. Lists of IP-using RMS of various technologies and methods for image processing. The basic methods of image processing. Shows the importance of using RMS crisp digital image, image processing to highlight significant information in the image and the mathematical analysis of the obtained data to solve problems. Shows the layout of a typical CPS. Shows the composition of a typical computer vision system. Analyzed the principle of operation of RMS in determining the product of the marriage. The sequence performed by the system of action. The basic steps for image processing in computer vision system. In the article the conclusion about expediency of use in the food industry RMS to develop high-tech automated intelligent expert systems for quality control of food raw materials, semi-finished and finished products.

Abstract
One of the mainreasons forthe microbiologicalspoilageof meatisnon-compliance withthe establishedtemperature conditions in the links ofthe cold chain, as well as unplannedtemperature variability cased byequipment malfunctionsor electrical networks failure, as well as with the human factor. This paper discusses thepossibilitiesof automationto control and predict the microbiologicalspoilagerisk for raw meatduring storage using the temperature as the main parameter for changing microbiological statusof raw meat. The analysis of the automated parameters has been performed. Among them: temperature and respecting time todifferent initialcontaminationof raw meat. The role of predictive mathematical model has been shown in the implementation and evaluation of the data got from monitoring meat storage conditions and in the identifying unacceptable risks and critical control points (CCP). Automationcontrolis carried by automatingoperations as part of the kinetic curveimage for microorganism population growth, processing the digitalandvisual information, mathematical calculations andconsistencyanalysis of the CCP measurements toestablishedcritical limits. A computerprogram (basicprinciples andstructure) has been implementedfor processing experimental dataandconstructingpredictedempirical models of bacterial contamination in order to manage the processes of microbiologicalspoilage. To determine thestart ofraw meatspoilage, predictive modelsare an alternative tothe numerousand costlymicrobiological researches. The effectivenessof computer system implementationis the errors reduction, as well as the benefitsin time andcostin securingraw meatduring storage.

Abstract
In this study, the best mixed feed was prepared by using the algorithm of particle swarm optimization (PSO) and by taking into account the breeding type and method of the poultries and various farm animals (cattle, sheep, rabbit), their needs, ages, and feeding costs and optimization them all. Algorithms were operated ten times for the same animal species, and certain conclusions were drawn from the recorded results. The most outstanding finding of the study was that particle swarm optimization behaved rather steadily in the solution of nonlinear problems. It was determined that genetic coded algorithm could not behave in a sufficiently steady way, and it stuck to local minimums. When the results were examined, it was observed that low-cost feed mixes having fewer penalties were available in linear programming in the solution of linear feed mix problems. According to results, particle swarm optimization produces more rapid and steady results having low penalty rates but its cost is slightly higher than real-coded genetic algorithm. Primary objective to be taken into consideration during the preparation of feed mixes is low penalty rate. Particle swarm optimization was accepted to produce better results than real-coded genetic algorithm as cost was a secondary factor to observe. However, it is observed that real-coded genetic algorithm and particle swarm optimization produce better results in the solution of nonlinear feed mix problems.

Abstract
The article shows that an important step in the production of cream candies is the process of cooking fondant syrup. The scheme of preparation of sugar fondant, as well as the basic operations of cooking fondant syrup dosage sugar syrup, molasses, milk and other ingredients, mixing and boiling of mixture prescription. A description of the main parameters affecting the process of cooking fondant syrup. Described their relationship to each other. To identify all parameters and conditions that influence the process of cooking fondant syrup, was designed structural - parametric model of the process of cooking fondant syrup. In the work produced structural - parametric modeling of the process of cooking fondant syrup, which is boiled down to the construction of matrices of relationships between grouped by state parameters and goals of the individual functional blocks of the system similarly to the parametric adjacency matrix. For this purpose, the original data were generated in the form of an array of random observations. Further, as a result of casual observations was made a set of statistical data and generated the table of correlations. Correlation, in turn, subjected to the test of significance by student's criterion, the resulting transformed matrix of correlation coefficients. The main task was to find comparable characteristics of relations between the state parameters of the technological system, and then build a situational model of the system state with the algorithmic procedures of identification and forecasting. Was defined statistical model of the process of cooking fondant syrup by the method of Protodyakonov. The coefficients of the equations were calculated using the program Method. According to the formula coefficients have been calculated multiple linear regression regression and composed the matrix of relationships that has been converted into a matrix comparable dimensionless characteristics of relations. As a result of subsequent mathematical permutations and calculations in article obtained optimal criterion for the quality of the process of cooking fondant syrup. In this work it is concluded that the proposed method of structural - parametric modeling allows you to determine the most informative parameters in the problem of structural - parametric modeling of the process of cooking fondant syrup and find the best criterion of its quality.

Abstract
In article aspects of the use of artificial intelligence technologies as a method of pattern recognition in the tasks of monitoring decision-making and technical diagnostics equipment grain processing enterprises. It is shown that the most perspective direction of development of monitoring systems is the use of intelligent methods of analysis of source diagnostic information. These methods include expert systems based on neural network data analysis methods. The use of intelligent systems for monitoring and technical diagnostics helps to increase efficiency and reliability of technological equipment. For the successful application of these technologies is necessary to have a large amount of statistical data on many parameters of the machines in various operating modes and technical conditions. There are development and theoretical researches of the intelligent monitoring system in Moscow State University of Food Production (MGUPP). There are practical researches to collect information characterizing various technical state of the researched machines on grain processing enterprises (feed and milling) in the Moscow region. The proposed system for monitoring and gathering information having distributed nature and constructed with the use of "cloud" technologies. Thus, the controlled equipment is equipped with a stationary system tolerable of collection of telemetry data (vibration, temperature, instantaneous values of current to motor circuit, the noise emitted by the machine during its operation). Further information is transmitted to a remote server through GSM technology for its storage and mathematical treatment. Currently designed a prototype monitoring system that continuously collect information in real time with functioning equipment. This approach allows us to accumulate the necessary statistics on the equipment to create a powerful knowledge base and the creation of neural networks. The results of research is the development of software and hardware of a stationary system of collection and processing of diagnostic information about the researched equipment. The block diagram of the automated monitoring of technological machines is shown. The procedure of collecting and analyzing diagnostic information using neural network data analysis tools program Statistica has been developed.

Abstract
In this article the necessity of solving the problem of automation of quality control of fondant masses, the most massive and popular categories of chocolates. It is shown that the most important process in the production of these sweets is the molding process. The conducted research has focused on the development of intelligent integrated expert system for monitoring structural and mechanical properties of fondant masses after molding with the use of vision systems. An important area of application of digital images recorded by a digital camera in the visible range, an automatic control of the main indicators kachestva color and shape of manufactured products. The article formulates the tasks required for achieving the set goal. Also presented proposals to ensure wide use of digital video camera as a smart sensor. The technique of preparation of digital videography and methods experimental video molding process harnesses fondant mass in industrial conditions. Developed, presented in the paper, the block diagram of the control algorithm on the basis of which an intelligent system takes the decision to change the regulatory impacts. Presents a model of the system of automatic regulation of the process of molding fondant harness developed in Simulink.

Abstract
The article reveals the use of technology multi-agent simulation modeling to predict and identify the processes that take place in high school at the time of transfer and accumulation of knowledge of the active elements. Enter a description of the block diagram in the form of system decomposition for further modeling. A mathematical description of the processes of knowledge creation and evaluation of the quality of education. Describes the use of means of expansion of multi-agent models by constructing an artificial neural network to improve the accuracy of calculations with the experiments with the model. The use of multi-agent simulation using mathematical models and artificial intelligence allows to reflect the status and dynamics of the process of accumulation and transfer of knowledge to the analysis and prediction of the quality of education. This article describes the methods and software implementation of agent-based simulation of interaction of the teacher and the student, taking into account the psycho-physiological, emotional and cognitive state of intelligent agents. Simulation results and their analysis.

Abstract
In terms of abundance in the country the number of suppliers of inputs has increased dramatically. Processing plants that depend on suppliers, trying to find the best option, which will satisfy all customer requirements. In a qualitative and not expensive raw products manufactured by the company, will largely determine the economic performance of the enterprise such as revenue, earnings and profitability. Therefore, before these enterprises especially acute question of choosing the most suitable resource provider. Mainly for processing enterprises must take into account the following parameters: the quality of incoming raw materials, conditions for the supply of raw materials", "price of raw materials received, a contractual basis. For this purpose was developed and proposed methodology for supplier selection for incoming quality parameters with the use of linguistic variables, subsystems inference in fuzzy set theory. The basis of this methodology lies in the system together with expert estimates. Fuzzy and linguistic variables are used in natural language description of the various objects and phenomena in the formalization of processes and decision-making in examining hard situations. The proposed methodology allows the user to take an appropriate decision on the choice of the Executive Order required to set parameters, to avoid getting poor quality of raw materials. Also, using the proposed methodology, the company will be able to automate the stage of acceptance of raw materials, to focus on the production of products, new product development and sale of goods on the market, the development of optimal logistic component. Taken together, all steps to automate the business processes of the enterprise, as a result, the company will provide a structured, independent largely on human factors and other outside influences.

Abstract
In response to growing consumer demands in the country at the moment there is a tendency to reduce the role of standard products, replacing them with products designed for specific groups of consumers. The country is in practice to maintain an assortment of such a production plan, which provides for the same release for each product. Same preferences of consumers in this approach is not recognized. The theory of fuzzy sets enables scheme solving problems in which judgment or evaluation play an important role in the evaluation of uncertainty. The intention of this theory was to build a functional correspondence between fuzzy linguistic descriptions and special functions, expressing a degree of membership values of measured parameters mentioned vague descriptions. L. Zadeh fuzzy sets defined as a tool for constructing theories of options. The technique of forming the range of products for companies based on the theory of fuzzy sets. Finding perspective nomenclature and structure of production ensures the formation of a trade enterprise core, which will be sold on the market with minimum risk, will ensure stable functioning of the enterprise and achieve its strategic goals. Also, using the proposed methodology, the company will be able to automate the phase of the sale of goods on the market, focus on the manufacture of products, new product development, development of optimal logistic component. Taken together, all steps to automate the business processes of the enterprise, as a result, the company will provide a structured, independent largely on human factors and other outside influences.

Abstract
The paper deals with the optimization of the animal feed ration problems and its solving by means of optimization algorithms. The objects of the survey are the following: to produce the mathematical problem determination of the linear programming, to lead the construction of the objective function, to choose the problem solving procedure, and to work out software for the method realization. The expectations of the survey are to find a functional and un expansive solution in the field of calculation processes which provides the calculation of the balanced nutrition in animal diet with the given specification. Input data, the received recipe and the software-based realization were performed with the use of the Microsoft Excel mathematical software, and the processing was produced with the use of the built-in algorithmical language VBA (Visual Basic for Application). As a result, the optimization in the form of total deviations decrease of nutrients content in the animals ration which allows getting the better balanced ration.

Abstract
Organoleptic tests in the food industry are becoming more and more important due to the increased competition in the grocery market. Price / performance ratio is in most cases determined by solving the consumer purchase. The use of modern methods of sensory evaluation allows the manufacturer to improve the quality of products and processes as well as the sensory tests are used in the evaluation of raw materials and semi-finished and finished products. Reasonable application of sensory techniques improves efficiency and effectiveness of processes. Quantitative descriptive and profile method allows to solve many problems of food products in the field of sensory analysis. Reasonable application of sensory techniques improves efficiency and effectiveness of processes. Quantitative descriptive and profile method allows to solve many problems of food products in the field of sensory analysis. Sensory evaluation by means of descriptive and profile analysis is carried out in several stages: preparation of test selection and selection of descriptors, estimate the intensity parameter descriptor identifying the final list of descriptors, test and build the profile of the product. The reliability of the results obtained, allowing to build the profile of the product is greatly influenced by the factor of accuracy of the estimate testers intensity descriptors. It largely depends on the ability of the test to extract the complex sensations incentives that reflect the analyzed descriptor and comparing through sensory memory with sensations obtained in training with reference substances and products. Due to the importance of similarity assessment testers same intensities at different sessions of the descriptors need to pay special attention to the organization of trainings. Quantitative descriptor-profile analysis is used in various areas of sensory analysis, in particular for a comprehensive assessment of the quality of food and the development of new customer relationship-oriented products and rebranding existing products.