A new position group contribution model is proposed for the estimation of normal boiling data of organic compounds involving a carbon chain from C2 to C18.The characteristic of this method is the use of position distr...A new position group contribution model is proposed for the estimation of normal boiling data of organic compounds involving a carbon chain from C2 to C18.The characteristic of this method is the use of position distribution function.It could distinguish most of isomers that include cis-or trans-structure from organic compounds.Contributions for hydrocarbons and hydrocarbon derivatives containing oxygen,nitrogen,chlorine,bromine and sulfur,are given.Compared with the predictions,results made use of the most common existing group contribution methods,the overall average absolute difference of boiling point predictions of 417 organic compounds is 4.2 K;and the average absolute percent derivation is 1.0%,which is compared with 12.3 K and 3.2% with the method of Joback,12.1 K and 3.1% with the method of Constantinou-Gani.This new position contribution groups method is not only much more accurate but also has the advantages of simplicity and stability.展开更多
A new method is proposed based on the position group contribution additivity for the prediction of melting points of covalent compounds. The characteristics of this method are the use of position distribution func-tio...A new method is proposed based on the position group contribution additivity for the prediction of melting points of covalent compounds. The characteristics of this method are the use of position distribution func-tion, which could distinguish between most isomers including cis or trans structure of organic compounds. Contri-butions for hydrocarbons and hydrocarbon derivatives containing oxygen, nitrogen, chlorine, bromine and sulfur, are given. Results are compared with those by the most commonly used estimating methods. The average derivation for prediction of normal melting temperature of 730 compounds is 14.46 K, compared to 29.33 K with the method of Joback, and 27.81 K with the method of Constantinou-Gani. The present method is not only more accurate, but also much simpler and more stable.展开更多
Localization is fundamental component for many critical applicationsin wireless sensor networks (WSNs). However, DV-Hop localization algorithmand its improved ones cannot meet the requirement of positioning accuracy f...Localization is fundamental component for many critical applicationsin wireless sensor networks (WSNs). However, DV-Hop localization algorithmand its improved ones cannot meet the requirement of positioning accuracy fortheir high localization errors. This paper proposes a localization algorithm basedon positioning group quality (LA-PGQ). The average estimate hop size was firstcorrected by link singularity and difference between the estimation hop lengthand true hop length among beacons, the best positioning group was constitutedfor unknown node by using node trust function and positioning group qualityevaluation function to choose three beacons with best topological distribution.Third, LA-PGQ algorithm uses two-dimensional hyperbolic algorithm instead ofthe classical three-side method/least square method to determine the coordinates ofnodes, which are more accurate. Simulation results show the positioning accuracyof LA-PGQ algorithm is obviously improved in WSNs, and the average localizationerror of LA-PGQ algorithm is remarkable lower than those of the DV-Hopalgorithm and its improved algorithm and Amorphous, under both the isotropyand anisotropy distributions.展开更多
文摘A new position group contribution model is proposed for the estimation of normal boiling data of organic compounds involving a carbon chain from C2 to C18.The characteristic of this method is the use of position distribution function.It could distinguish most of isomers that include cis-or trans-structure from organic compounds.Contributions for hydrocarbons and hydrocarbon derivatives containing oxygen,nitrogen,chlorine,bromine and sulfur,are given.Compared with the predictions,results made use of the most common existing group contribution methods,the overall average absolute difference of boiling point predictions of 417 organic compounds is 4.2 K;and the average absolute percent derivation is 1.0%,which is compared with 12.3 K and 3.2% with the method of Joback,12.1 K and 3.1% with the method of Constantinou-Gani.This new position contribution groups method is not only much more accurate but also has the advantages of simplicity and stability.
文摘A new method is proposed based on the position group contribution additivity for the prediction of melting points of covalent compounds. The characteristics of this method are the use of position distribution func-tion, which could distinguish between most isomers including cis or trans structure of organic compounds. Contri-butions for hydrocarbons and hydrocarbon derivatives containing oxygen, nitrogen, chlorine, bromine and sulfur, are given. Results are compared with those by the most commonly used estimating methods. The average derivation for prediction of normal melting temperature of 730 compounds is 14.46 K, compared to 29.33 K with the method of Joback, and 27.81 K with the method of Constantinou-Gani. The present method is not only more accurate, but also much simpler and more stable.
基金This work was supported by the Yunnan Local Colleges Applied BasicResearch Projects(2017FH001-059,2018FH001-010,2018FH001-061)National Natural Science Foundation of China(61962033).
文摘Localization is fundamental component for many critical applicationsin wireless sensor networks (WSNs). However, DV-Hop localization algorithmand its improved ones cannot meet the requirement of positioning accuracy fortheir high localization errors. This paper proposes a localization algorithm basedon positioning group quality (LA-PGQ). The average estimate hop size was firstcorrected by link singularity and difference between the estimation hop lengthand true hop length among beacons, the best positioning group was constitutedfor unknown node by using node trust function and positioning group qualityevaluation function to choose three beacons with best topological distribution.Third, LA-PGQ algorithm uses two-dimensional hyperbolic algorithm instead ofthe classical three-side method/least square method to determine the coordinates ofnodes, which are more accurate. Simulation results show the positioning accuracyof LA-PGQ algorithm is obviously improved in WSNs, and the average localizationerror of LA-PGQ algorithm is remarkable lower than those of the DV-Hopalgorithm and its improved algorithm and Amorphous, under both the isotropyand anisotropy distributions.
