scholarly journals The use of multicriteria optimization method in selecting protoclones in the population of the ‘Kokur Belyi’ grape variety

2021 ◽  
pp. 336-343
Author(s):  
Н.Л. Студенникова ◽  
З.В. Котоловець
Keyword(s):  
Multicriteria Optimization ◽  
Target Function ◽  
Optimization Method ◽  
Grape Variety ◽  
Units Of Measurement ◽  
Selection Of ◽  
The Ideal

В статье представлены данные по 11 биолого-хозяйственным признакам 100 маточных кустов винограда сорта Кокур белый за 2019-2021 гг. Исследования проводились на производственном участке сорта винограда Кокур белый (№ 361, формировка АЗОС-1, схема посадки 3×1,25) в филиале «Алушта» АО «ПАО «Массандра». По средним показателям за три года исследований методом многокритериальной оптимизации отобраны 25 протоклонов сорта Кокур белый (протоклоны первого вегетативного поколения) с наименьшими показателями функции в диапазоне от φ=3,330 до φ=6,103. Выбор лучшего куста определялся из условий наибольшего приближения к идеалу, т.е. интервал [φ(xi); xu]→min. Следовательно, чем меньше значение функции протоклона φ(xi), тем лучше куст. Значения целевых функций сравнивались у 100 кустов, затем отбирались протоклоны по наименьшим показателям, определяющим лучшие кусты. Применение метода многокритериальной оптимизации обеспечивает объективный подход при отборе протоклонов, исключая единицы измерения изучаемых признаков, преобразуя их в безразмерный вид. Для дальнейшего исследования с выделенных 25 кустов винограда сорта Кокур белый будет проведена заготовка лозы для проведения настольной прививки с последующей закладкой клоноиспытательного участка первого вегетативного поколения сорта Кокур белый. The article presents data on 11 biological and economical traits of 100 mother vines of the ‘Kokur Belyi’ for the period of 2019-2021. The research was carried out at the production plot of the ‘Kokur Belyi’ grape variety (No. 361, AZOS-1 pruning, planting scheme 3 × 1.25) in the Alushta branch of FSUE PJSC Massandra. According to the average of indicators for three years of research using method of multicriteria optimization, we selected 25 protoclones of the ‘Kokur Belyi’ variety (protoclones of the first vegetative voltine) with the lowest function indicators in the range from φ = 3.330 to φ = 6.103. The choice of the best bush was determined from the conditions of the closest approximation to the ideal, i.e. interval [φ(x); x]→min. Therefore, the smaller the value of the protoclone function φ(x), the better the bush. Target function values for 100 bushes were compared, after that protoclones were separated by the lowest indicators, determining the best bushes. The use of multicriteria optimization method provides an objective approach to the selection of protoclones, excluding the units of measurement of the studied characteristics, converting them into a nondimensional form. For further research, from the selected 25 bushes of grapes of the ‘Kokur Belyi’ variety, vines will be gathered for table grafting, followed by the establishment of a clone-testing plot of the first vegetative voltine of the ‘Kokur Belyi’ variety.

scholarly journals Complex selection of the best collection of chick-peaby method of multi-criterian optimization anh Harrington's reliable function

2019 ◽  
Vol 2019 (1) ◽  
pp. 81-88
Author(s):  
A.E. Titova
Keyword(s):  
Plant Height ◽  
Multicriteria Optimization ◽  
Comparative Evaluation ◽  
Oil Content ◽  
Desirability Function ◽  
Evaluation Criteria ◽  
Optimization Method ◽  
Plant Weight ◽  
Cicer Arietinum L ◽  
Selection Of

A comprehensive selection of the best collection sample of chickpeas by the method of multicriteria optimization and by the Harrington desirability function in seven varieties of chickpeas - Cicer arietinum L., C. Reticulatum Labizinsky., C. Judaicum Boiss., C. Bijugum K.N. Rech., C. Pinnatifidum Jaub., C. chorassinicum (Bge) M. Pop., C. yamashitae Kitam by the comparative evaluation of the alternatives by a set of the indicators of resistance to diseases and pests, the number of beans per plant, the number of grains in the bean, the number of grains per plant, the mass of grains per plant, the weight of 1000 grains, plant height, height of the lower bean, protein and oil content has been made. A set of evaluation criteria has been defined. The analysis of similar criteria at application of a method of multicriteria optimization (geometrical check of criteria) has been used. The importance of selections on a number of the indicators of productivity and adaptability to the environmental conditions for successful selection work in order to improve the economically valuable signs of chickpeas has been analyzed. Key words: complex selection, multicriteria optimization method, Harrington desirability function, plant height, lower bean attachment height, number of beans, number of grains per plant, weight of grain per plant, number of grains in a bean, weight of 1000 grains.

Providing of lateral clearance in tooth gears by additional displacement of the original contour

2021 ◽  
pp. 13-18
Author(s):  
Keyword(s):  
Multicriteria Optimization ◽  
Optimization Method ◽  
Cylindrical Gears ◽  
Tooth Gear ◽  
Lateral Clearance ◽  
Gear Wheels ◽  
Selection Of

A method of multicriteria optimization of gearing with the use of the Kompas-3D program for calculating the degrees of correction of the lateral clearance in the tooth gear is proposed. The recommendations (GOST 16532—70, Appendix 2) on the selection of the degrees of correction of the gear wheels of cylindrical gears are analyzed, the necessary corrections are proposed. Keywords: tooth gear, lateral clearance, degree of correction, multicriteria optimization method, Kompas-3D program, blocking contournhanthong [email protected]

The DQE of an electron image recording system

1978 ◽  
Vol 36 (1) ◽  
pp. 100-101
Author(s):  
K.-H. Herrmann ◽  
D. Krahl ◽  
H.-P Rust
Keyword(s):  
Primary Electron ◽  
Ideal Case ◽  
Image Recording ◽  
Main Requirement ◽  
High Detection ◽  
Electron Image ◽  
Video Amplifier ◽  
Detection Quantum Efficiency ◽  
Selection Of ◽  
The Ideal

The high detection quantum efficiency (DQE) is the main requirement for an imagerecording system used in electron microscopy of radiation-sensitive specimens. An electronic TV system of the type shown in Fig. 1 fulfills these conditions and can be used for either analog or digital image storage and processing [1], Several sources of noise may reduce the DQE, and therefore a careful selection of various elements is imperative.The noise of target and of video amplifier can be neglected when the converter stages produce sufficient target electrons per incident primary electron. The required gain depends on the type of the tube and also on the type of the signal processing chosen. For EBS tubes, for example, it exceeds 10. The ideal case, in which all impinging electrons create uniform charge peaks at the target, is not obtainable for several reasons, and these will be discussed as they relate to a system with a scintillator, fiber-optic and photo-cathode combination as the first stage.

scholarly journals Identification of the Optimum Environments for the High Yield and Quality Traits of Lentil Genotypes Evaluated in Multi-Location Trials

2021 ◽  
Vol 13 (15) ◽  
pp. 8247
Author(s):  
Dimitrios N. Vlachostergios ◽  
Christos Noulas ◽  
Anastasia Kargiotidou ◽  
Dimitrios Baxevanos ◽  
Evangelia Tigka ◽  
...  
Keyword(s):  
Crude Protein ◽  
Agronomic Traits ◽  
High Yield ◽  
Breeding Programs ◽  
Growing Seasons ◽  
Yield And Quality ◽  
Food And Feed ◽  
Superior Genotypes ◽  
Selection Of ◽  
The Ideal

Lentil is a versatile and profitable pulse crop with high nutritional food and feed values. The objectives of the study were to determine suitable locations for high yield and quality in terms of production and/or breeding, and to identify promising genotypes. For this reason, five lentil genotypes were evaluated in a multi-location network consisting of ten diverse sites for two consecutive growing seasons, for seed yield (SY), other agronomic traits, crude protein (CP), cooking time (CT) and crude protein yield (CPY). A significant diversification and specialization of the locations was identified with regards to SY, CP, CT and CPY. Different locations showed optimal values for each trait. Locations E4 and E3, followed by E10, were “ideal” for SY; locations E1, E3 and E7 were ideal for high CP; and the “ideal” locations for CT were E3 and E5, followed by E2. Therefore, the scope of the cultivation determined the optimum locations for lentil cultivation. The GGE-biplot analysis revealed different discriminating abilities and representativeness among the locations for the identification of the most productive and stable genotypes. Location E3 (Orestiada, Region of Thrace) was recognized as being optimal for lentil breeding, as it was the “ideal” or close to “ideal” for the selection of superior genotypes for SY, CP, CT and CPY. Adaptable genotypes (cv. Dimitra, Samos) showed a high SY along with excellent values for CP, CT and CPY, and are suggested either for cultivation in many regions or to be exploited in breeding programs.

Parameter study and optimization design of a hat oblique tunnel portal

2021 ◽  
pp. 095440972110140
Author(s):  
Zijian Guo ◽  
Tanghong Liu ◽  
Wenhui Li ◽  
Yutao Xia
Keyword(s):  
High Speed ◽  
Optimization Design ◽  
Pareto Front ◽  
Optimization Problem ◽  
Optimization Method ◽  
Design Parameters ◽  
Parameter Study ◽  
Buffer Structure ◽  
Tunnel Entrance ◽  
The Ideal

The present work focuses on the aerodynamic problems resulting from a high-speed train (HST) passing through a tunnel. Numerical simulations were employed to obtain the numerical results, and they were verified by a moving-model test. Two responses, [Formula: see text] (coefficient of the peak-to-peak pressure of a single fluctuation) and[Formula: see text] (pressure value of micro-pressure wave), were studied with regard to the three building parameters of the portal-hat buffer structure of the tunnel entrance and exit. The MOPSO (multi-objective particle swarm optimization) method was employed to solve the optimization problem in order to find the minimum [Formula: see text] and[Formula: see text]. Results showed that the effects of the three design parameters on [Formula: see text] were not monotonous, and the influences of[Formula: see text] (the oblique angle of the portal) and [Formula: see text] (the height of the hat structure) were more significant than that of[Formula: see text] (the angle between the vertical line of the portal and the hat). Monotonically decreasing responses were found in [Formula: see text] for [Formula: see text] and[Formula: see text]. The Pareto front of [Formula: see text] and[Formula: see text]was obtained. The ideal single-objective optimums for each response located at the ends of the Pareto front had values of 1.0560 for [Formula: see text] and 101.8 Pa for[Formula: see text].

scholarly journals A New Hyper-Parameter Optimization Method for Power Load Forecast Based on Recurrent Neural Networks

Algorithms ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 163
Author(s):  
Yaru Li ◽  
Yulai Zhang ◽  
Yongping Cai
Keyword(s):  
Neural Networks ◽  
Parameter Optimization ◽  
Recurrent Neural Networks ◽  
Critical Role ◽  
Optimization Method ◽  
Bayesian Optimization ◽  
Power Load ◽  
Gradient Calculation ◽  
Truncated Newton ◽  
Selection Of

The selection of the hyper-parameters plays a critical role in the task of prediction based on the recurrent neural networks (RNN). Traditionally, the hyper-parameters of the machine learning models are selected by simulations as well as human experiences. In recent years, multiple algorithms based on Bayesian optimization (BO) are developed to determine the optimal values of the hyper-parameters. In most of these methods, gradients are required to be calculated. In this work, the particle swarm optimization (PSO) is used under the BO framework to develop a new method for hyper-parameter optimization. The proposed algorithm (BO-PSO) is free of gradient calculation and the particles can be optimized in parallel naturally. So the computational complexity can be effectively reduced which means better hyper-parameters can be obtained under the same amount of calculation. Experiments are done on real world power load data,where the proposed method outperforms the existing state-of-the-art algorithms,BO with limit-BFGS-bound (BO-L-BFGS-B) and BO with truncated-newton (BO-TNC),in terms of the prediction accuracy. The errors of the prediction result in different models show that BO-PSO is an effective hyper-parameter optimization method.

Classifying the “ideal migrant worker”

Focaal ◽  
2010 ◽  
Vol 2010 (57) ◽  
pp. 79-94 ◽  
Author(s):  
Janet McLaughlin
Keyword(s):  
Migrant Worker ◽  
Global Capitalism ◽  
Migration Program ◽  
English Speaking ◽  
Multiple Levels ◽  
Seasonal Agricultural Workers ◽  
Seasonal Agricultural Workers Program ◽  
Selection Of ◽  
The Ideal

This article analyzes the ideology and practice of multi-unit competition that pervades neoliberal subjectivities and produces the “ideal” flexible worker within contemporary global capitalism. It demonstrates how state and capitalist interests converge to influence the selection of the ideal transnational migrant worker, how prospective migrants adapt to these expectations, and the consequences of such enactments, particularly for migrants, but also for the societies in which they live and work. Multiple levels of actors—employers, state bureaucrats, and migrants themselves—collude in producing the flexible, subaltern citizen, which includes constructions and relations of class, race, gender, and nationality/citizenship. The case study focuses on Mexican and Jamaican participants in Canada's Seasonal Agricultural Workers Program, a managed migration program that legally employs circular migrant farmworkers from Mexico and several English-speaking Caribbean countries in Canadian agriculture.

GIS Based Multi-Criteria decision support system and machine learning for Hospital Site Selection case study Oran - Algeria

2022 ◽  
Vol 14 (1) ◽  
pp. 0-0
Keyword(s):  
Site Selection ◽  
Decision Makers ◽  
Analysis Method ◽  
Automatic Learning ◽  
Hospital Site ◽  
Set Up ◽  
High Level ◽  
Selection Of ◽  
The Ideal

The selection of hospital sites is one of the most important choice a decision maker has to take so as to resist the pandemic. The decision may considerably affect the outbreak transmission in terms of efficiency , budget, etc. The main targeted objective of this study is to find the ideal location where to set up a hospital in the willaya of Oran Alg. For this reason, we have used a geographic information system coupled to the multi-criteria analysis method AHP in order to evaluate diverse criteria of physiological positioning , environmental and economical. Another objective of this study is to evaluate the advanced techniques of the automatic learning . the method of the random forest (RF) for the patterning of the hospital site selection in the willaya of Oran. The result of our study may be useful to decision makers to know the suitability of the sites as it provides a high level of confidence and consequently accelerate the power to control the COVID19 pandemic.

scholarly journals Selection of the variant solution of forest road alignment conceptual design using multicriteria optimisation

2009 ◽  
pp. 165-176 ◽  
Author(s):  
Bogdan Stefanovic ◽  
Ivan Bjelanovic
Keyword(s):  
Conceptual Design ◽  
Multicriteria Optimization ◽  
Linear Distribution ◽  
Forest Road ◽  
Multicriteria Optimisation ◽  
Technical Production ◽  
The Given ◽  
Selection Of ◽  
Design Construction ◽  
Building Parameters

One of the three studied variant solutions of forest road conceptual design was selected based on the linear distribution of criteria, as the method of multicriteria optimization. The selection was performed with 25 parameters classified as economic, technical, production and social criteria. The parameters of technical criteria were grouped into design, construction and building parameters. Based on calculated nominal values of parameters by the given criteria, their ranking, comparison, point rating and scoring, the selected most favorable solution was variant 1.

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