scholarly journals ЭФФЕКТИВНОСТЬ И ЕДИНСТВО ПОСЕВНЫХ И УБОРОЧНЫХ КОМПЛЕКСОВ В ЗЕРНОВОМ ПОДКОМПЛЕКСЕ

2019 ◽  
Author(s):  
N.V. Byshov ◽  
V.A. Makarov ◽  
O.V. Makarova ◽  
S.V. Gasparyan ◽  
A.V. Shemyakin
Keyword(s):  
Mathematical Model ◽  
Cost Function ◽  
Systematic Approach ◽  
Weather Conditions ◽  
Tabular Form ◽  
Work Intensity ◽  
Daily Work ◽  
Work Plan ◽  
Grain Crops ◽  
The Cost

В статье используется системный подход при рассмотрении проведения полевых работ посадочными и уборочными комплексами. Установлено, что для полноценного использования возможностей посадочных и уборочных комплексов при минимальных затратах механизированные работы необходимо проводить при максимальных значениях коэффициентов использования сменного времени. В табличной форме представлены значения коэффициентов использования сменного времени для условий Нечернозёмной зоны России. Выбор стратегии проведения работ определяют скорость созревания, погодные условия, наличие технических средств. Предлагаются численные составы посадочных и уборочных комплексов в расчёте на 1 га, которые представляются в табличной форме при агрегатировании с тракторами класса 1,423. Оценка эффективности функционирования комплексов должна строиться с учетом деятельности всех подсистем по выполнению плана работ. Такой оценкой ежедневной работы комплекса может служить коэффициент напряженности работ, равный отношению сумм фактически выполненных работ к запланированным,. В выводах установлены пути совершенствования механизированных процессов на посеве и уборке зерновых культур, а в качестве оптимального варианта выбран вариант максимального использования времени смены за счет внедрения новых организационнотехнических форм. В итоге разработана математическая модель функционирования посевных и уборочных комплексов при производстве зерновых культур для Нечернозёмной зоны России, которая может быть использована и для других регионов.The article uses a systematic approach when considering the management of planting and harvesting subcomplexes. It has been established that in order to fully utilize the capabilities of planting and harvesting complexes while minimizing the cost function, it should be carried out at maximum values of utilization factors of replaceable time. The tabular form presents the values of the utilization factors of the replaceable time for the conditions of the Nonchernozem zone of Russia. The choice of work strategy determines the speed of ripening, weather conditions, the availability of technical means. The numerical compositions of the planting and harvesting complexes are calculated for 1 ha and are presented in tabular form for the composition of the aggregates when aggregated with tractors of class 1,4,2,3. Evaluation of the functioning of the complexes should take into account the activities of all subsystems for the implementation of the work plan. Such an assessment of the daily work of the complex can serve as a coefficient of work intensity, equal to the ratio of the amounts of work actually performed to the planned, calculated per machine i. The conclusions set out ways to improve the processes at sowing and harvesting grain crops, and as the main option, an option was chosen to improve the use of shift time by introducing new organizational and technical forms. As a result, a mathematical model of the functioning of sowing and harvesting complexes in the production of grain crops for the Nonchernozem zone of Russia has been developed, which can be used for other regions.

A Method for Inferring the Optimization Cost Function of Experimentally Observed Motor Strategies

2005 ◽  
Author(s):  
Carlo L. Bottasso ◽  
Alessandro Croce ◽  
Stefano Sartirana ◽  
Boris I. Prilutsky
Keyword(s):  
Experimental Data ◽  
Mathematical Model ◽  
Cost Function ◽  
Motor Task ◽  
Computational Procedure ◽  
Search Space ◽  
Optimality Criteria ◽  
Cost Functions ◽  
The Cost ◽  
Motor Strategies

We propose a computational procedure for inferring the cost functions that, according to the Principle of Optimality, underlie experimentally observed motor strategies. This work tries to overcome the need to hypothesize the cost functions, extracting this non-directly observable information from experimental data. Optimality criteria of observed motor tasks are here indirectly derived using: a) a mathematical model of the bio-system; and b) a parametric mathematical model of the possible cost functions, i.e. a search space constructed in such a way as to presumably contain the unknown function that was used by the bio-system in the given motor task of interest. The cost function that best matches the experimental data is identified within the search space by solving a nested optimization problem. This problem can be recast as a non-linear programming problem and therefore solved using standard techniques. The proposed methodology is tested on representative examples.

scholarly journals Sustainability in management accounting: Modelling profit forecasting

2009 ◽  
Vol 6 (4) ◽  
pp. 201-209
Author(s):  
Rozainun Abdul Aziz ◽  
D.F. Percy ◽  
Faizal Mohamed Yusof
Keyword(s):  
Mathematical Model ◽  
Probability Distribution ◽  
Cost Function ◽  
Forecast Accuracy ◽  
Postal Survey ◽  
Back Issue ◽  
Bayesian Methodology ◽  
Sustainable Performance ◽  
Survey Form ◽  
The Cost

An insight into a mathematical model proposed is given in concept with the hope that both academicians and practitioners will progress in achieving forecast accuracy. The paper also attempts to give explanations for and cost effects of imperfect forecasts, an oversight which frequently occurs to management, a necessity in sustainability. Previous observations through pilot study, postal survey, case study and a follow-up survey form as a basis in formulating the mathematical model (Aziz-Khairulfazi, 2004). We use of probability distribution against point forecasts, the cost function and fundamentals of Bayesian methodology in approach towards sustainable performance. The model explains the use of probability distribution against point forecasts, the cost function and fundamentals of Bayesian methodology in approach towards sustainable performance. The paper will give explanations for and cost effects of imperfect forecasts, an oversight which frequently occurs to management. We relate our findings to the service and manufacturing industries and we include an important input to support our modelling, i.e. feed back issue. We conclude our study by highlighting the use of simple modeling that will benefit business organizations, thereafter influence performance and sustainability, an optiont organizations can also apply. This paper offers an innovative approach and a new flavour in examining an operational framework to a business scenario via profit forecasting model.

HARROWING OF SPRING GRAIN CROPS ON DRAINED LANDS

1970 ◽  
pp. 32-36
Author(s):  
Yu. I. Mitrofanov ◽  
L. V. Pugacheva ◽  
Т. N. Panteleeva ◽  
N. А. Smirnova
Keyword(s):  
Crop Yield ◽  
Humus Content ◽  
Weather Conditions ◽  
Soil Environment ◽  
Grain Crops ◽  
Weed Infestation ◽  
Tver Region ◽  
The Right ◽  
The Cost ◽  
The Impact

The studies were conducted on the experimental fields of the FGBNU VNIIMZ (Tver region). The soil is sod-podzolic, light loamy and sandy gley, drained; humus content - 1.8-2.6%, the supply of nutrients - medium and high, the reaction of the soil environment - slightly acidic and close to neutral. The article discusses the impact of agrotechnical methods and herbicides on weed infestation and crop yield of spring grain crops. It was established that the right and timely pre-emergence harrowing of crops on the impact on yield is practically not inferior to the action of herbicides. The technical efficiency in the number of weeds from the use of herbicide was 60.6%, from a single pre-emergence harrowing - 41.0%, from a double one - 55.7%. It is shown that the efficiency of pre-emergence harrowing, its stability in years of different weather conditions, can be improved using the method of "delayed" sowing of spring grain crops. The technical effectiveness of harrowing with delayed sowing, compared with the control, where the harrowing was carried out on ordinary sowings without delay, increased by 33.6-38.8%, in some experiments in the number of weeds it was more than 70%. With equal yields, the cost of processing 1 hectare of crops with herbicides is 4-6 times higher than the cost of a single harrow and 2-3 times on a double harrow. To create non-herbicidal technologies for growing spring grain crops on drained lands, the method of sowing in ribbons on the ridges is of interest: the yield increases, the contamination of crops decreases.

Modernization of Water Treatment System at Agricultural Enterprises Due to Introduction of Solar Energy

2020 ◽  
Vol 67 (1) ◽  
pp. 142-147
Author(s):  
Alina A. Aleksandrova ◽  
Maksim S. Zhuzhin ◽  
Yuliya M. Dulepova
Keyword(s):  
Mathematical Model ◽  
Water Treatment ◽  
Solar Energy ◽  
Energy Saving ◽  
Electric Energy ◽  
Solar Water Heater ◽  
Water Heater ◽  
Agricultural Enterprises ◽  
Solar Water ◽  
The Cost

Energy saving today is an integral part of the development strategy of agricultural organizations. Considerable attention is paid to the modernization and automation of technological processes in agricultural enterprises, which can improve the quality of work and reduce the cost of production. The direction of modernization is to reduce the consumption of electric energy by improving the water treatment system in livestock complexes. (Research purpose) The research purpose is to determine the potential of solar energy used in the Nizhny Novgorod region and to determine the possibility of its use for water heating in livestock complexes and to consider the cost-effectiveness of using a device to heat water through solar energy. (Materials and methods) Authors used an improved algorithm of Pixer and Laszlo, applied in the NASA project «Surface meteorology and Energy», which allows to calculate the optimal angle of inclination of the device for heating water. (Results and discussion) Designed a mock-up of a livestock complex with a solar water heater installed on the roof, protected by patent for invention No. 2672656. A mathematical model was designed experimentally to predict the results of the plant operation in non-described modes. (Conclusions) The article reveales the optimal capacity of the circulation pump. Authors have created a mathematical model of the device that allows to predict the water heating in a certain period of time. The article presents the calculations on the energy and economic efficiency of using a solar water heater. An electric energy saving of about 30 percent, in the economic equivalent of 35 percent.

scholarly journals An Adaptive Optimization Method Based on Learning Rate Schedule for Neural Networks

2021 ◽  
Vol 11 (2) ◽  
pp. 850
Author(s):  
Dokkyun Yi ◽  
Sangmin Ji ◽  
Jieun Park
Keyword(s):  
Artificial Intelligence ◽  
Cost Function ◽  
Numerical Experiments ◽  
Global Minimum ◽  
Optimization Method ◽  
Learning Method ◽  
Adaptive Optimization ◽  
The Cost ◽  
Proof Of Convergence ◽  
Learning Data

Artificial intelligence (AI) is achieved by optimizing the cost function constructed from learning data. Changing the parameters in the cost function is an AI learning process (or AI learning for convenience). If AI learning is well performed, then the value of the cost function is the global minimum. In order to obtain the well-learned AI learning, the parameter should be no change in the value of the cost function at the global minimum. One useful optimization method is the momentum method; however, the momentum method has difficulty stopping the parameter when the value of the cost function satisfies the global minimum (non-stop problem). The proposed method is based on the momentum method. In order to solve the non-stop problem of the momentum method, we use the value of the cost function to our method. Therefore, as the learning method processes, the mechanism in our method reduces the amount of change in the parameter by the effect of the value of the cost function. We verified the method through proof of convergence and numerical experiments with existing methods to ensure that the learning works well.

Erbium/Ytterbium-Doped Waveguide Amplifier (EYDWA) for extended reach of Wavelength Division Multiplexing based free space optics system (WDM/FSO)

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Bentahar Attaouia ◽  
Kandouci Malika ◽  
Ghouali Samir
Keyword(s):  
Wavelength Division Multiplexing ◽  
Free Space ◽  
Cost Effective ◽  
Weather Conditions ◽  
Free Space Optical ◽  
Wavelength Division ◽  
Space Optics ◽  
Effective Implementation ◽  
Transmission Distance ◽  
The Cost

AbstractThis work is focused to carry out the investigation of wavelength division multiplexing (WDM) approach on free space optical (FSO) transmission systems using Erbium Ytterbium Doped Waveguide Amplifier (EYDWA) integrated as post-or pre-amplifier for extending the reach to 30 Km for the cost-effective implementation of FSO system considering weather conditions. Furthermore, the performance of proposed FSO-wavelength division multiplexing (WDM) system is also evaluated on the effect of varying the FSO range and results are reported in terms of Q factor, BER, and eye diagrams. It has been found that, under clear rain the post-amplification was performed and was able to reach transmission distance over 27 Km, whereas, the FSO distance has been limited at 19.5 Km by using pre-amplification.

Sorting permutations by fragmentation-weighted operations

2020 ◽  
Vol 18 (02) ◽  
pp. 2050006 ◽  
Author(s):  
Alexsandro Oliveira Alexandrino ◽  
Carla Negri Lintzmayer ◽  
Zanoni Dias
Keyword(s):  
Approximation Algorithms ◽  
Computational Biology ◽  
Cost Function ◽  
Traditional Approach ◽  
Upper Bounds ◽  
Evolutionary Distance ◽  
Lower And Upper Bounds ◽  
Approximation Factor ◽  
New Type ◽  
The Cost

One of the main problems in Computational Biology is to find the evolutionary distance among species. In most approaches, such distance only involves rearrangements, which are mutations that alter large pieces of the species’ genome. When we represent genomes as permutations, the problem of transforming one genome into another is equivalent to the problem of Sorting Permutations by Rearrangement Operations. The traditional approach is to consider that any rearrangement has the same probability to happen, and so, the goal is to find a minimum sequence of operations which sorts the permutation. However, studies have shown that some rearrangements are more likely to happen than others, and so a weighted approach is more realistic. In a weighted approach, the goal is to find a sequence which sorts the permutations, such that the cost of that sequence is minimum. This work introduces a new type of cost function, which is related to the amount of fragmentation caused by a rearrangement. We present some results about the lower and upper bounds for the fragmentation-weighted problems and the relation between the unweighted and the fragmentation-weighted approach. Our main results are 2-approximation algorithms for five versions of this problem involving reversals and transpositions. We also give bounds for the diameters concerning these problems and provide an improved approximation factor for simple permutations considering transpositions.

Maximum Likelihood Ensemble Filter: Theoretical Aspects

2005 ◽  
Vol 133 (6) ◽  
pp. 1710-1726 ◽  
Author(s):  
Milija Zupanski
Keyword(s):  
Maximum Likelihood ◽  
Data Assimilation ◽  
Cost Function ◽  
Ensemble Data Assimilation ◽  
Error Covariance ◽  
Ensemble Data ◽  
Analysis Error ◽  
Nonlinear Observation ◽  
The Cost ◽  
Maximum Likelihood Ensemble Filter

Abstract A new ensemble-based data assimilation method, named the maximum likelihood ensemble filter (MLEF), is presented. The analysis solution maximizes the likelihood of the posterior probability distribution, obtained by minimization of a cost function that depends on a general nonlinear observation operator. The MLEF belongs to the class of deterministic ensemble filters, since no perturbed observations are employed. As in variational and ensemble data assimilation methods, the cost function is derived using a Gaussian probability density function framework. Like other ensemble data assimilation algorithms, the MLEF produces an estimate of the analysis uncertainty (e.g., analysis error covariance). In addition to the common use of ensembles in calculation of the forecast error covariance, the ensembles in MLEF are exploited to efficiently calculate the Hessian preconditioning and the gradient of the cost function. A sufficient number of iterative minimization steps is 2–3, because of superior Hessian preconditioning. The MLEF method is well suited for use with highly nonlinear observation operators, for a small additional computational cost of minimization. The consistent treatment of nonlinear observation operators through optimization is an advantage of the MLEF over other ensemble data assimilation algorithms. The cost of MLEF is comparable to the cost of existing ensemble Kalman filter algorithms. The method is directly applicable to most complex forecast models and observation operators. In this paper, the MLEF method is applied to data assimilation with the one-dimensional Korteweg–de Vries–Burgers equation. The tested observation operator is quadratic, in order to make the assimilation problem more challenging. The results illustrate the stability of the MLEF performance, as well as the benefit of the cost function minimization. The improvement is noted in terms of the rms error, as well as the analysis error covariance. The statistics of innovation vectors (observation minus forecast) also indicate a stable performance of the MLEF algorithm. Additional experiments suggest the amplified benefit of targeted observations in ensemble data assimilation.

scholarly journals An Optimized Mathematical Model for Items Supplies Planning of a Logistic System

2016 ◽  
Vol 10 (10) ◽  
pp. 133
Author(s):  
Mohammad Ali Nasiri Khalili ◽  
Mostafa Kafaei Razavi ◽  
Morteza Kafaee Razavi
Keyword(s):  
Mathematical Model ◽  
Mixed Integer ◽  
Logistics System ◽  
Proposed Model ◽  
Multiple Objective Decision Making ◽  
System Requirements ◽  
Purchasing Logistics ◽  
The Cost ◽  
The Mathematical Model ◽  
First Time

Items supplies planning of a logistic system is one of the major issue in operations research. In this article the aim is to determine how much of each item per month from each supplier logistics system requirements must be provided. To do this, a novel multi objective mixed integer programming mathematical model is offered for the first time. Since in logistics system, delivery on time is very important, the first objective is minimization of time in delivery on time costs (including lack and maintenance costs) and the cost of purchasing logistics system. The second objective function is minimization of the transportation supplier costs. Solving the mathematical model shows how to use the Multiple Objective Decision Making (MODM) can provide the ensuring policy and transportation logistics needed items. This model is solved with CPLEX and computational results show the effectiveness of the proposed model.

Using the cost function to generate Marshallian demand systems

2000 ◽  
Vol 25 (2) ◽  
pp. 209-227 ◽  
Author(s):  
Keith R. McLaren ◽  
Peter D. Rossitter ◽  
Alan A. Powell
Keyword(s):  
Cost Function ◽  
Demand Systems ◽  
The Cost
Sign in / Sign up

Export Citation Format

Share Document