Machine Learning for Hybrid Line Stability Ranking Index in Polynomial Load Modeling under Contingency Conditions

In the conventional technique,in the evaluation of the severity index,clustering and loading suffer from more iteration leading to more com-putational delay.Hence this research article identifies,a novel progression for fast predicting the severity of the line and clustering by incorporating machine learning aspects.The polynomial load modelling or ZIP(constant impedances(Z),Constant Current(I)and Constant active power(P))is developed in the IEEE-14 and Indian 118 bus systems considered for analysis of power system security.The process of finding the severity of the line using a Hybrid Line Stability Ranking Index(HLSRI)is used for assisting the concepts of machine learning with J48 algorithm,infers the superior affected lines by adopting the IEEE standards in concern to be compensated in maintaining the power system stability.The simulation is performed in the WEKA environment and deals with the supervisor learning in order based on severity to ensure the safety of power system.The Unified Power Flow Controller(UPFC),facts devices for the purpose of compensating the losses by maintaining the voltage characteristics.The finite element analysis findings are compared with the existing procedures and numerical equations for authentications.

The breeding of two polyploid rice lines with the characteristic of polyploid meiosis stability

Polyploidization is a basic feature of plant evolution. Nearly all of the main food, cotton and oil crops are polyploid. When ploidy levels increase, yields double; this phenomenon suggested a new strategy of rice breeding that utilizes wide crosses and polyploidization dual advantages to breed super rice. Because low seed set rates in polyploid rice usually makes it difficult to breed, the selection of Ph-liked gene lines was emphasized. After progenies of indica-japonica were identified and selected, two poly- ploid lines, PMeS-1 and PMeS-2 with Polyploid Meiosis Stability (PMeS) genes were bred. The proce- dure included seven steps: selecting parents, crossing or multiple crossing, back-crossing, doubling chromosomes, identifying the polyploid, and choosing plants with high seed set rates that can breed themselves into stable lines. The characteristics of PMeS were determined by observing meiotic be- haviors and by cross-identification of seed sets. PMeS-1 and PMeS-2, (japonica rice), have several characteristics different from other polyploid rice lines, including a higher rate of seed set (more than 65%, increasing to more than 70% in their F1 offspring); and stable meiotic behaviors (pairing with bi- valents and quarivalents nearly without over-quarivalent in prophase, nearly without lagging chromo- somes in metaphase and without micronuclei in anaphase and telophase). The latter was obviously different from control polyploid line Dure-4X, which displayed abnormal meiotic behaviors including a higher rate of multivalents, univalents and trivalents in prophase, lagging chromosomes in metaphase and micronuclei in anaphase and telophase. There were also three differences of the breeding method between PMeS lines and normal diploid lines: chromosomes doubling, polyploidism identifying and higher seed set testing. The selection of PMeS lines is the first step in polyploid rice breeding; their use will advance the progress of polyploid rice breeding, which will in turn offer a new way to breed super rice.

Passive sonar identification (Ⅱ): Stability and uniqueness of line spectrum

This series of papers deal with vessel recoghtion. This paper is the second of the paper series. It focuses on how to memorize the stable features of line spectrum of specific vessels by using line spectrum pattern plate and on related problems. This paper examines the analyzing parameters of line spectrum: average times, time length and their impact on the occurrence of stable lines. It compares the impact of two dtherellt average times on the occurrence of stable lines (occurrence ratio > 70%) and unstable lines, and shows that it takes longer time span for average when stable lines for recoghtion are used. Moreover, the paper discusses the statistic methods of establishing line spectrum pattern plate usihg stable lines,including the definition of stability and related para-meters. The stability of line spectrum and the uniqueness of stable lines are investigated in over 1000 samples gathered from 43 vessels in 65 operating conditions (with an original recording time of 3.5 hours). The results demonstrate the statistical implication of such uniqueness. The average overlapping ratio is 5 %; the proportion of vessels without stable lines is 8 %. Studies also show that the richness of line spectrums is not an identifying feature, distinguishing type A vessels from type B vessels