Improved Particle Swarm Optimization Algorithm for Optimization of Power Communication Network

Yuhuai Wang,Qihui Wang,Huixi Zhang,Kang An,Xia Ye,Yaping Sun 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.1

Based on particle swarm optimization (PSO) algorithm and its power system reactive power optimization method to in-depth study and research proposed a new hybrid particle swarm optimization algorithm (HPSO). Algorithm combines the differential evolution algorithm and simulated annealing algorithm and particle swarm optimization algorithm, in particle searching optimal except for tracking individual and global, and tracks produced by particle information difference of the three value. At the same time, when the particle search space of one dimension speed lower than the setting value will be re initialized the dimensional particle velocity and the particle of differential evolution mutation. For the crossover and mutation operations, new solution may be worse than the original solution to, the introduction of simulated annealing algorithm, the metropolis rule in a certain extent accept bad solutions, allows the target function in a certain degree of deterioration, practical calculation is not according to the probability to choose the poor solution, but rather the judgment target function difference is less than allows the target function deterioration range. Hybrid particle swarm optimization algorithm combines the advantages of particle swarm optimization algorithm, differential evolution algorithm and simulated annealing algorithm, to maintain the diversity of particles, has very strong practicability.

Research on the Management Strategy of the Last Level Cache Sharing Multi-Core Processor

Yuhuai Wang,Huixi Zhang,Yaping Sun,Qihui Wang 보안공학연구지원센터 2015 International Journal of Grid and Distributed Comp Vol.8 No.5

Effective allocation of shared resources limited is a key problem for chip multiprocessors. As the processor core growth in the scale, multi thread for the shared resource limited system competition will become more intense, the performance of the system will also be more significant. In order to alleviate this problem, a fair and effective multi thread shared resources allocation scheduling algorithm is important. In all kinds of shared resources, the largest effect on the system performance is the shared cache and DRAM system. There are essential differences between the last level cache and a cache. The goal of a cache design is to provide fast data processor which requires high access speed. However, the object of the last level cache is to save data in the chip as much as possible, and the access speed requirements are not too high, it is more subject to the plate number of available transistors. Management level cache LRU strategy and its approximate algorithm are not applicable to the large capacity last level cache for traditional. It may cause destructive interference between threads, cache thrashing of stream media program lead, which will lead to a decline in the performance of processor. This paper focuses on the analysis of some hot problems of the last level cache management in the process of the large capacity of multi-core platform sharing, and puts forward the corresponding costs less.

Load Forecasting Research of Power System Based on Fuzzy Sets Algorithm

Qihui Wang,Yuhuai Wang,Huixi Zhang,Yaping Sun 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.6

In this paper, adjust the system parameters back-propagation algorithm based on fuzzy similarity interval type proposed by the fuzzy rule base to streamline redundant fuzzy sets, we can also merge with the means to reduce the number of redundant fuzzy rules, then singular value decomposition method is preferred fuzzy rules. The algorithm can effectively eliminate the adverse effects caused by redundant fuzzy rule, which improve the interpretability of fuzzy rules to reduce the computational complexity of the fuzzy reasoning process, and to improve the approximation accuracy of the system. Based on the long-term and short-term load power load characteristics analysis, to identify the influence of the load itself changes and related factors, gray system theory, neural network model and chaotic time series methods, models and methods for forecasting power load range were research. Examples verified, interval prediction has better precision, demonstrate the effectiveness of the interval prediction algorithm, the research results can be used in power market analysis and forecasting systems, power system operation and provide scientific basis for management decisions.

The role of long noncoding RNAs in livestock adipose tissue deposition - A review

Wang, Lixue,Xie, Yuhuai,Chen, Wei,Zhang, Yu,Zeng, Yongqing Asian Australasian Association of Animal Productio 2021 Animal Bioscience Vol.34 No.7

With the development of sequencing technology, numerous, long noncoding RNAs (lncRNAs) have been discovered and annotated. Increasing evidence has shown that lncRNAs play an essential role in regulating many biological and pathological processes, especially in cancer. However, there have been few studies on the roles of lncRNAs in livestock production. In animal products, meat quality and lean percentage are vital economic traits closely related to adipose tissue deposition. However, adipose tissue accumulation is also a pivotal contributor to obesity, diabetes, atherosclerosis, and many other diseases, as demonstrated by human studies. In livestock production, the mechanism by which lncRNAs regulate adipose tissue deposition is still unclear. In addition, the phenomenon that different animal species have different adipose tissue accumulation abilities is not well understood. In this review, we summarize the characteristics of lncRNAs and their four functional archetypes and review the current knowledge about lncRNA functions in adipose tissue deposition in livestock species. This review could provide theoretical significance to explore the functional mechanisms of lncRNAs in adipose tissue accumulation in animals.

Identification and functional prediction of long noncoding RNAs related to intramuscular fat content in Laiwu pigs

Wang Lixue,Xie Yuhuai,Chen Wei,Zhang Yu,Zeng Yongqing 아세아·태평양축산학회 2022 Animal Bioscience Vol.35 No.1

Objective: Intramuscular fat (IMF) is a critical economic indicator of pork quality. Studies on IMF among different pig breeds have been performed via high-throughput sequencing, but comparisons within the same pig breed remain unreported. Methods: This study was performed to explore the gene profile and identify candidate long noncoding RNA (lncRNAs) and mRNAs associated with IMF deposition among Laiwu pigs with different IMF contents. Based on the longissimus dorsi muscle IMF content, eight pigs from the same breed and management were selected and divided into two groups: a high IMF (>12%, H) and low IMF group (<5%, L). Whole-transcriptome sequencing was performed to explore the differentially expressed (DE) genes between these two groups. Results: The IMF content varied greatly among Laiwu pig individuals (2.17% to 13.93%). Seventeen DE lncRNAs (11 upregulated and 6 downregulated) and 180 mRNAs (112 upregulated and 68 downregulated) were found. Gene Ontology analysis indicated that the following biological processes played an important role in IMF deposition: fatty acid and lipid biosynthetic processes; the extracellular signal-regulated kinase cascade; and white fat cell differentiation. In addition, the peroxisome proliferator-activated receptor, phosphatidylinositol- 3-kinase-protein kinase B, and mammalian target of rapamycin pathways were enriched in the pathway analysis. Intersection analysis of the target genes of DE lncRNAs and mRNAs revealed seven candidate genes associated with IMF accumulation. Five DE lncRNAs and 20 DE mRNAs based on the pig quantitative trait locus database were identified and shown to be related to fat deposition. The expression of five DE lncRNAs and mRNAs was verified by quantitative real time polymerase chain reaction (qRT-PCR). The results of qRT-PCR and RNA-sequencing were consistent. Conclusion: These results demonstrated that the different IMF contents among pig individuals may be due to the DE lncRNAs and mRNAs associated with lipid droplets and fat deposition. Objective: Intramuscular fat (IMF) is a critical economic indicator of pork quality. Studies on IMF among different pig breeds have been performed via high-throughput sequencing, but comparisons within the same pig breed remain unreported.Methods: This study was performed to explore the gene profile and identify candidate long noncoding RNA (lncRNAs) and mRNAs associated with IMF deposition among Laiwu pigs with different IMF contents. Based on the longissimus dorsi muscle IMF content, eight pigs from the same breed and management were selected and divided into two groups: a high IMF (>12%, H) and low IMF group (<5%, L). Whole-transcriptome sequencing was performed to explore the differentially expressed (DE) genes between these two groups.Results: The IMF content varied greatly among Laiwu pig individuals (2.17% to 13.93%). Seventeen DE lncRNAs (11 upregulated and 6 downregulated) and 180 mRNAs (112 upregulated and 68 downregulated) were found. Gene Ontology analysis indicated that the following biological processes played an important role in IMF deposition: fatty acid and lipid biosynthetic processes; the extracellular signal-regulated kinase cascade; and white fat cell differentiation. In addition, the peroxisome proliferator-activated receptor, phosphatidylinositol-3-kinase-protein kinase B, and mammalian target of rapamycin pathways were enriched in the pathway analysis. Intersection analysis of the target genes of DE lncRNAs and mRNAs revealed seven candidate genes associated with IMF accumulation. Five DE lncRNAs and 20 DE mRNAs based on the pig quantitative trait locus database were identified and shown to be related to fat deposition. The expression of five DE lncRNAs and mRNAs was verified by quantitative real time polymerase chain reaction (qRT-PCR). The results of qRT-PCR and RNA-sequencing were consistent.Conclusion: These results demonstrated that the different IMF contents among pig individuals may be due to the DE lncRNAs and mRNAs associated with lipid droplets and fat deposition.