“…Most of the scientists [2,3,4] inclined to believe that the artificial intelligence -is algorithm of actions a highly organized matter, which is endowed personality and ability to receive, data storage and processing information, generate new knowledge and independent decision making relative to set her developer objectives and goals . If we talk about artificial personality, in its structure have to be of substructures of solving problems objective (Law), subjective (feeling) and irrational (faith) content.…”
Section: Analysis Of the Latest Research And Publicationsmentioning
The purpose. To formalize main positions and to specify perspectives of development of intellectual automaticcontrol systems over production processes of farming industry. Methods. Analysis of opportunities of heightening efficiency of agroindustrial production and problem of building artificial intellect for control of engineering systems. Synthesis of general structure of neuro-similar net of integral system of on-line control over agricultural production processes and principles of formation of database for its provision. Results. The structure of intellectual component of automatic-control system over the production process, architecture of engineering neuro-similar net is specified. Principles of construction of algorithm of automatic formation of control action of production process on the basis of restoring knowledge base are generalized. Conclusions. Basic gain in yield of agricultural products from unit of cultivated area is possible at heading new intellectual technologies of production. The level of artificial intellect in guidance systems over technological processes of farming industry can be limited by use of theories of evaluations and logic. The key job of building intellectual guidance systems of production processes of farming industry nowadays is formalization of knowledge base.
Key words: technological operations, system of integrated control, elements of artificial intelligence, knowledge base.Problem. Further substantial increase of efficiency of agricultural production is only possible at the expense of operational and purposeful quality management of execution technological operations of cultivation of alive facilities -soil, plants, animals. In this regard further development technical providing for agricultural manufacturing will be based on the creation of new technological equipment, the main feature of which lies in automatically change operating modes of working bodies on the basis of operational information for achievement of optimal phase condition of the object that the is being processed. It is obvious that simple substitution of the human expert on linear systems of automatic control respective working bodies, in this case, already has inadequate -are necessary elements of artificial intelligence for the cultivation of large volumes of diverse information and better decision making.
Analysis of the latest research and publications.The technical essence of the new level of automation is to move from the reactive a principle of work automatic systems for the deviation of individual parameters for complex multi management, with the active involvement of object information from cultivation, environmental, technical and specialized databases.There are different models of formalization of human intelligence.[1] One of the most classic can be considered a model which identical to the processes adapt of biological organisms to their environment. These programs do not resolve the problem by means of logical reasoning but create system solutions, which compete with each other for get the...
“…Most of the scientists [2,3,4] inclined to believe that the artificial intelligence -is algorithm of actions a highly organized matter, which is endowed personality and ability to receive, data storage and processing information, generate new knowledge and independent decision making relative to set her developer objectives and goals . If we talk about artificial personality, in its structure have to be of substructures of solving problems objective (Law), subjective (feeling) and irrational (faith) content.…”
Section: Analysis Of the Latest Research And Publicationsmentioning
The purpose. To formalize main positions and to specify perspectives of development of intellectual automaticcontrol systems over production processes of farming industry. Methods. Analysis of opportunities of heightening efficiency of agroindustrial production and problem of building artificial intellect for control of engineering systems. Synthesis of general structure of neuro-similar net of integral system of on-line control over agricultural production processes and principles of formation of database for its provision. Results. The structure of intellectual component of automatic-control system over the production process, architecture of engineering neuro-similar net is specified. Principles of construction of algorithm of automatic formation of control action of production process on the basis of restoring knowledge base are generalized. Conclusions. Basic gain in yield of agricultural products from unit of cultivated area is possible at heading new intellectual technologies of production. The level of artificial intellect in guidance systems over technological processes of farming industry can be limited by use of theories of evaluations and logic. The key job of building intellectual guidance systems of production processes of farming industry nowadays is formalization of knowledge base.
Key words: technological operations, system of integrated control, elements of artificial intelligence, knowledge base.Problem. Further substantial increase of efficiency of agricultural production is only possible at the expense of operational and purposeful quality management of execution technological operations of cultivation of alive facilities -soil, plants, animals. In this regard further development technical providing for agricultural manufacturing will be based on the creation of new technological equipment, the main feature of which lies in automatically change operating modes of working bodies on the basis of operational information for achievement of optimal phase condition of the object that the is being processed. It is obvious that simple substitution of the human expert on linear systems of automatic control respective working bodies, in this case, already has inadequate -are necessary elements of artificial intelligence for the cultivation of large volumes of diverse information and better decision making.
Analysis of the latest research and publications.The technical essence of the new level of automation is to move from the reactive a principle of work automatic systems for the deviation of individual parameters for complex multi management, with the active involvement of object information from cultivation, environmental, technical and specialized databases.There are different models of formalization of human intelligence.[1] One of the most classic can be considered a model which identical to the processes adapt of biological organisms to their environment. These programs do not resolve the problem by means of logical reasoning but create system solutions, which compete with each other for get the...
“…There are other less popular methods used by researchers that can be used to calculate the capacity given off by a battery [7,8]. After analyzing them, we can conclude that they, as a rule, are different combinations or just special cases of expressions (1)(2)(3)(4).…”
Section: Introductionmentioning
confidence: 99%
“…However, it is worth noting here that in the empirical dependence of Aguf (3), the coefficients presented are arbitrary empirical constants. In dependence (7) obtained by expanding into a Taylor series, the coefficients are dependent constants. Based on the above, it can be argued that dependence (3) is independent and empirical.…”
The paper presents studies of the empirical Korovin-Skundin equations, the generalized Peikert equation, the porous electrode equation and the probability integral. After that, it is proved that these equations can be used to estimate the capacity of nickel-cadmium accumulator at different discharge currents. The relations (4, 6, 8, 9) presented in the work fully correspond to the obtained experimental data with and have a relative error of no more than 6%, which is quite an acceptable fact for practical calculations. However, the parameters in these ratios depend on the capacity of the batteries under study, which is not an entirely acceptable fact in their practical application. It is shown that the Peikert, Libenov, Aguf and Khaskina-Danilenko equations cannot be used to calculate the capacity given off by the battery according to the considered changes in the discharge current. It has been established that the Peikert, Libenov and Aguf equations have an inversely proportional dependence for the discharged capacity on the discharge current, but such a dependence appears only starting from the inflection point and to infinity, and for SBM brand batteries, the inflection point of the curve C(i) is at the current i = 1Cn. In addition, it is shown that the Haskina-Danilenko equation cannot be used in the entire range of discharge currents considered in the work, since it is valid only in the range from zero to discharge currents, starting from which the battery capacity begins to drop sharply. It is established that the parameters of these equations depend on the capacity of the batteries, and this is a disadvantage in their practical application.
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