Research on Fire Power Distribution Model of Shore Support Based on PSGA

2014 ◽  
Vol 543-547 ◽  
pp. 747-750
Author(s):  
Xiang Yang Li ◽  
Wan Feng Ji ◽  
Hai Feng Xu ◽  
Chang Peng Pan
Keyword(s):  
Genetic Algorithms ◽  
Power Distribution ◽  
Distribution Model ◽  
Model Based ◽  
Improved Algorithm

As for the two main limitations as partial constringency and convergence hysteresis of Genetic Algorithms (GA), predatory search is introduced and Predatory Search Genetic Algorithms (PSGA) based on GA is designed to enhance the integrate ability of hunting. The concepts of fire support platform and target fitness are introduced, and fire power distribution model based on fire support fitness coefficient is built. The improved PSGA is applied to fire power and emulation experiment is done. The result of emulation shows the validity of the improved algorithm.

scholarly journals RELATION BETWEEN PORE MODEL AND CENTER-LINE TEMPERATURE IN HIGH BURN-UP UO2 PELLET

2010 ◽  
Vol 7 (2) ◽  
pp. 147-153
Author(s):  
Suwardi Suwardi
Keyword(s):  
Thermal Properties ◽  
Temperature Distribution ◽  
Power Distribution ◽  
Distribution Model ◽  
Center Line ◽  
Pore Model ◽  
Pellet Temperature ◽  
Typical Data ◽  
Line Temperature ◽  
Centerline Temperature

Relation between pore model and center-line temperature of high burn up UO2 Pellet. Temperature distribution has been evaluated by using different model of pore distribution. Typical data of power distribution and coolant data have been chosen in this study. Different core model and core distribution model have been studied for related temperature, in correlation with high burn up thermal properties. Finite element combined finite different adapted from Saturn-1 has been used for calculating the temperature distribution. The center-line temperature for different pore model and related discussion is presented.   Keywords: pore model, high burn up, UO2 pellet, centerline temperature.

scholarly journals SIS dynamic network model based on product semantics from the perspective of infectious disease dynamics

2021 ◽  
Vol 235 ◽  
pp. 03035
Author(s):  
jiaojiao Lv ◽  
yingsi Zhao
Keyword(s):  
Network Model ◽  
Purchase Intention ◽  
Recommendation System ◽  
Optimal Algorithm ◽  
Dynamic Network ◽  
Distribution Model ◽  
Recommendation Algorithm ◽  
Model Based ◽  
Dynamic Network Model ◽  
Recommendation Algorithms

Recommendation system is unable to achive the optimal algorithm, recommendation system precision problem into bottleneck. Based on the perspective of product marketing, paper takes the inherent attribute as the classification standard and focuses on the core problem of “matching of product classification and recommendation algorithm of users’ purchase demand”. Three hypotheses are proposed: (1) inherent attributes of the product directly affect user demand; (2) classified product is suitable for different recommendation algorithms; (3) recommendation algorithm integration can achieve personalized customization. Based on empirical research on the relationship between characteristics of recommendation information (independent variable) and purchase intention (dependent variable), it is concluded that predictability and difference of recommendation information are not fully perceived and stimulation is insufficient. Therefore, SIS dynamic network model based on the distribution model of SIS virus is constructed. It discusses the spreading path of recommendation information and “infection” situation of consumers to enhance accurate matching of recommendation system.

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