09. Materials of Conferences and Seminars
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Browsing 09. Materials of Conferences and Seminars by Subject "algorithms"
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Item Open Access Applying machine learning models for predicting forest fires in Australia and the influence of weather on the spread of fires based on satellite and weather forecast data(2020 International Young Scholars Workshop, 2020) Meraliyev B.; Kongratbayev K.Abstract What shall we expect from the year 2020? The coronavirus pandemic is not the worst thing that humanity can face in the near future. According to the observations of the scientists, in March, 2020, the planet temperature warmed up to the record-high level. Also, the temperature of the world’s oceans exceeded its average temperatures by 80%, and prognosis of the meteorological observations is not good. The warming seas had already led to catastrophic disaster. The average temperature increase can also lead to hurricanes, drought, invasion of locusts and, the worst, to forest fires. Natural disasters lead to loss of life, destruction of properties and infrastructure, loss of animal natural habitats, displacement of humans. And the results of these all lead to humanitarian catastrophes, including social and economic. The situations related to the nature are always very serious, as the whole world is involved. This is like butterfly effect, i.e., the natural disaster in Australia affect the economic and ecologic situation in USA and England. Taking the Australia, they faced problem that cannot be avoided. Nevertheless, the world can be prepared and prevent from the huge disasters. The forecasting of forest fires can really be helpful, as well as the inquiry of the weather impact on fires. The current paper is focused on the study of fire forecasting and weather influence on fire. The relevance of the study is important, as the global warming and human caused fires are increasing and there is a trend that Australia’s fires became more dangerous and longer lasting. The artificial intelligence, particularly machine learning algorithms, can help to make appropriate calculations and predictions to safe the ecosystem and human lives. According to the preliminary research results we acquire; in-depth multidimensional analysis confirms almost 100 percent dependence of bushfires on the weather conditions. Using the machine learning algorithms, it would be possible to predict the time and positioning of inflammation source.Item Open Access The Automation of Course Scheduling in Higher Education Institutions: Mathematical methods and software products(2020 International Young Scholars Workshop, 2020) Aitchanov B.; Baimuratov O.; Rustauletov B.Abstract. The formation and management of schedules is repetitive and troublesome for any class, university and organization. Limited resources in terms of people, time and locations. Institutions needs solutions that will meet all of these constraints of scheduling. That system for scheduling should take in control the scheduling process which takes time by automatically allocating time slots for teaching and creating course schedule. And easily can be integrated with their systems without need to do some extra work like adding data for scheduling or exporting them, reducing the time spend on creating schedules and minimizing errors that made by people. Today, there are various types of systems and services designed to create schedules, reserve classrooms, assign classrooms for course teachers at specific times. The use of modern technologies, methods and models makes it easy to use open applications and services, as well as services at the local level. This paper presents the results of the analysis of systems. Their structures, algorithms, models, and also functional capabilities. The aim of this work is to determine the types of applications and systems, analysis of various options for the implementation of algorithms for the formation of schedules in educational institutions.