Abstract: In this work, the methods of artificial intelligence are analyzed in order to perform a more accurate value prediction of the apartments sold in Vilnius city and district. The work uses publicly available information about apartments put for sale on Aruodas.l

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Abstract: The article presents a comparable analysis of the results of solving problems in Šiauliai city (the 2nd Stage) mathematics olympiads for the 5th grade students throughout 2016-–2019. It aims to find out whether school students selected for olympiads at differ

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Abstract: The article makes observations on some of the problems in the first part of the 2014–2022 state- level maturity examination in Lithuania. It discusses solutions to such problems without and with a calculator. These observations are intended to draw attention

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Abstract: The purpose of the article is to familiarize teachers and students with the fundamental theorem of algebra for real polynomials and its proof. Polynomials of small degrees are considered separately. It is showed how equations of the third and fourth degree ca

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Abstract: In this work, the aspects of the task of the state maturity exam in mathematics (structure and content of the program) and the change of students’ achievements (difficulty of the tasks and differentiating factor) in 2012–2021 are analyzed. Between 2012 and 20

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Abstract: The problem of the existence of a triangle with respect to three given elements in some cases can be very difficult. For example, Brokard’s problem about the existence of a triangle, given its three bisectors 1, has a long history 3 and solved only in 1994 10

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Abstract: High-quality mathematics instruction for all means high expectations and strong support for all students. An insightful math teaching policy when apdating both school math curriculum and as- sessment system as well as mathematics teacher training and in-servi

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Abstract: In the work, relevant methods of stock price forecasting are applied and compared: statistical time series (ARIMA, SARIMA) and neural network-based (LSTM). The results of stock price (Ama- zon, Apple, Google, Netflix, and Tesla companies) simulations are eval

Summary: Darbe yra pritaikomi ir palyginami akcijų kainų prognozavimo metodai: sta- tistiniai laiko eilučių metodai (ARIMA, SARIMA) bei neuroniniais tinklais grįstas metodas (LSTM). Bendrovių Amazon, Apple, Google, Netflix ir Tesla akcijų kainų modeliavimo rezul- tata

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