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Abstract. The number of experts who realize the importance of big data continues to increase in various fields of the economy. Experts begin to use big data more frequently for the solution of their specific objectives. One of the probable big data tasks in the construction industry is the determination of the probability of contract execution at a stage of its establishment. The contract holder cannot guarantee execution of the contract. Therefore it leads to a lot of risks for the customer. This article is devoted to the applicability of machine learning methods to the task of determination of the probability of a successful contract execution. Authors try to reveal the factors influencing the possibility of contract default and then try to define the following corrective actions for a customer. In the problem analysis, authors used the linear and non-linear algorithms, feature extraction, feature transformation and feature selection. The results of investigation include the prognostic models with a predictive force based on the machine learning algorithms such as logistic regression, decision tree, randomize forest. Authors have validated models on available historical data. The developed models have the potential for practical use in the construction organizations while making new contracts.

To date, there is no doubt about the need and possibilities of using large amounts of information. So called “Big Data" technology is used in a variety of areas, and urban planning is no exception. The article discusses how to use large amounts of information for a competent design of social and engineering urban networks in the interests of cities residents while preserving historical appearance of cities. The proposed hypothesis states that urban planning can transition to a new higher level with the introduction of "Big Data" technology based on the concept of "Smart City", which not only makes the life of residents comfortable, but also allows making timely adjustments to one or other urban process with the purpose of its improvement. Additionally, possible approaches of the concept implementation and their applicability under various conditions are discussed. The article analyzes the experience of Smart City concept implementation as a part of "Big Data" technologies in practice of a number of European cities. Important positive results of such implementation are noted. The role and place of each of the parties interested in sustainable development of the city, in the development of intellectual systems for managing this development is discussed. In particular, a lot of attention is paid to the role of the state as the initiator and coordinator of interaction between the parties, the main holder and user of data, services and infrastructure. It is concluded that the potential built into the "Big Data" technology will allow us to move to a new level of urban planning, based on real urban data collected by various technical means.

The method of productiion of the composite selenium-graphitic electrodes based on organic polymer binder was proposed. Electrochemical behavior of the elementary selenium as content of composite electrode in sulfuric acid medium was assessed. A formation of hydrogen selenide during the cathode polarization, and formation of selenite and selenate ions was shown. An influence of potential spread velocity, acid concentration, and temperature of electrolyte were evaluated. Effective activation power for cathode process was estimated using the temperature-cathodic method.