Modeling and forecasting of principal minerals production

2021 ◽  
Vol 14 (9) ◽  
Author(s):  
Sunila Saadat ◽  
Ijaz Hussain ◽  
Muhammad Faisal
Author(s):  
Юлия Владимировна Татаркова ◽  
Татьяна Николаевна Петрова ◽  
Олег Валериевич Судаков ◽  
Александр Юрьевич Гончаров ◽  
Ольга Николаевна Крюкова

В настоящей статье представлен обзор основных решений, доступных сегодня для формирования как краткосрочных, так и долгосрочных проекций заболеваемости болезней глаза и его придаточного аппарата в студенческой среде. С другой стороны, существует ряд проблем, связанных с многообразием факторов, влияющих на заболеваемость, статистической необоснованностью и противоречивостью имеющихся результатов анализа данных. Представлены результаты математического моделирования зависимости показателя заболеваемости от наиболее влиятельных факторов образовательной и социальной среды. Перечислены важнейшие направления разработки математических моделей распространения заболеваемости. С помощью разработанного программного комплекса проведена серия вычислительных экспериментов по оценке и прогнозированию заболеваемости обучающихся в вузах разного профиля. Показана эффективность применения методики многовариантного моделирования и прогнозирования, указаны их ограничения и возможности практического применения. По расположению обобщенной области благоприятного прогноза в факторном пространстве можно определить время воздействия неблагоприятных для зрения факторов, которое должно составлять не более 10 ... 11 часов в сутки, количество профилактических мероприятий должно составлять не менее 3 ... 4. При этом риск развития миопии составит не более 0,4, вероятность усталости глаз за компьютером составит не более 0,4, вероятность дискомфорта глаз на занятиях составит не более 0,15. Исходя из характера прогноза, определяется длительность диспансерного наблюдения, а также потребность профилактических мероприятий по устранению или ослаблению действия неблагоприятно влияющих социально-гигиенических и медико-биологических факторов конкретного больного. Использование прогностической матрицы в практическом здравоохранении позволяет существенно улучшить работу по профилактике офтальмологической заболеваемости и является одним из эффективных мероприятий диспансеризации студенческой молодежи, так как дает возможность выделить из числа обучающихся группу с высоким риском неблагоприятного исхода заболевания This article provides an overview of the main solutions available today for the formation of both short-term and long-term projections of the incidence of eye diseases and its adnexa in the student environment. On the other hand, there are a number of problems associated with a variety of factors affecting the incidence, statistical unreasonability and inconsistency of the available data analysis results. The results of mathematical modeling of the dependence of the incidence rate on the most influential factors of the educational and social environment are presented. The most important areas of developing mathematical models for the spread of morbidity are listed. With the help of the developed software package, a series of computational experiments was carried out to assess and predict the incidence of students in universities of various profiles. The effectiveness of the application of multivariate modeling and forecasting methods is shown, their limitations and practical application possibilities are indicated. By the location of the generalized region of favorable prognosis in the factor space, it is possible to determine the exposure time of factors unfavorable for vision, which should be no more than 10 ... 11 hours a day, the number of preventive measures should be at least 3 ... 4. At the same time, the risk of development myopia will be no more than 0.4, the probability of eye fatigue at the computer will be no more than 0.4, the likelihood of eye discomfort in the classroom will be no more than 0.15. Based on the nature of the forecast, the duration of the follow-up observation is determined, as well as the need for preventive measures to eliminate or weaken the action of adverse social, hygienic and biomedical factors of a particular patient. The use of the prognostic matrix in practical health care can significantly improve the work on the prevention of ophthalmic morbidity and is one of the effective medical examinations for students, since it makes it possible to distinguish among the students a group with a high risk of an unfavorable outcome of the disease


Author(s):  
Daniel Mitchell ◽  
Patrick L. Brockett ◽  
Rafael Mendoza-Arriaga ◽  
Kumar Muthuraman

Axioms ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 18
Author(s):  
Marouane Mahrouf ◽  
Adnane Boukhouima ◽  
Houssine Zine ◽  
El Mehdi Lotfi ◽  
Delfim F. M. Torres ◽  
...  

The novel coronavirus disease (COVID-19) pneumonia has posed a great threat to the world recent months by causing many deaths and enormous economic damage worldwide. The first case of COVID-19 in Morocco was reported on 2 March 2020, and the number of reported cases has increased day by day. In this work, we extend the well-known SIR compartmental model to deterministic and stochastic time-delayed models in order to predict the epidemiological trend of COVID-19 in Morocco and to assess the potential role of multiple preventive measures and strategies imposed by Moroccan authorities. The main features of the work include the well-posedness of the models and conditions under which the COVID-19 may become extinct or persist in the population. Parameter values have been estimated from real data and numerical simulations are presented for forecasting the COVID-19 spreading as well as verification of theoretical results.


Insects ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 168
Author(s):  
Xueqin Liu ◽  
Hui Wang ◽  
Dahan He ◽  
Xinpu Wang ◽  
Ming Bai

Beetles are key insect species in global biodiversity and play a significant role in steppe ecosystems. In the temperate steppe of China, the increasing degeneration of the grasslands threatens beetle species and their habitat. Using Generalized Additive Models (GAMs), we aimed to predict and map beetle richness patterns within the temperate steppe of Ningxia (China). We tested 19 environmental predictors including climate, topography, soil moisture and space as well as vegetation. Climatic variables (temperature, precipitation, soil temperature) consistently appeared among the most important predictors for beetle groups modeled. GAM generated predictive cartography for the study area. Our models explained a significant percentage of the variation in carabid beetle richness (79.8%), carabid beetle richness distribution seems to be mainly influenced by temperature and precipitation. The results have important implications for management and conservation strategies and also provides evidence for assessing and making predictions of beetle diversity across the steppe.


2021 ◽  
Vol 5 (1) ◽  
pp. 46
Author(s):  
Mostafa Abotaleb ◽  
Tatiana Makarovskikh

COVID-19 is one of the biggest challenges that countries face at the present time, as infections and deaths change daily and because this pandemic has a dynamic spread. Our paper considers two tasks. The first one is to develop a system for modeling COVID-19 based on time-series models due to their accuracy in forecasting COVID-19 cases. We developed an “Epidemic. TA” system using R programming for modeling and forecasting COVID-19 cases. This system contains linear (ARIMA and Holt’s model) and non-linear (BATS, TBATS, and SIR) time-series models and neural network auto-regressive models (NNAR), which allows us to obtain the most accurate forecasts of infections, deaths, and vaccination cases. The second task is the implementation of our system to forecast the risk of the third wave of infections in the Russian Federation.


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