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Study on Rank Reversals in Liner Allocation Method

Zhang Ling,Zhou Dequn

Strategic Study of CAE 2008, Volume 10, Issue 2, Pages 50-53

Abstract:

The problem that the liner allocation method can result in rank reversalconcepts of sorting vectors and their relativity distribute ra tios are proposed to explain the causes of rank

Keywords： decision making liner allocation method rank reversal rank preservation

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Using heterogeneous patent network features to rank and discover influential inventors

Yong-ping DU,Chang-qing YAO,Nan LI

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 7, Pages 568-578 doi: 10.1631/FITEE.1400394

Abstract: Most classic network entity sorting algorithms are implemented in a homogeneous network, and they are not applicable to a heterogeneous network. Registered patent history data denotes the innovations and the achievements in different research fields. In this paper, we present an iteration algorithm called inventor-ranking, to sort the influences of patent inventors in heterogeneous networks constructed based on their patent data. This approach is a flexible rule-based method, making full use of the features of network topology. We sort the inventors and patents by a set of rules, and the algorithm iterates continuously until it meets a certain convergence condition. We also give a detailed analysis of influential inventor’s interesting topics using a latent Dirichlet allocation (LDA) model. Compared with the traditional methods such as PageRank, our approach takes full advantage of the information in the heterogeneous network, including the relationship between inventors and the relationship between the inventor and the patent. Experimental results show that our method can effectively identify the inventors with high influence in patent data, and that it converges faster than PageRank.

Keywords： Heterogeneous patent network Influence Rule-based ranking

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A critical review of ash slagging mechanisms and viscosity measurement for low-rank coal and bio-slags

Md Tanvir ALAM, Baiqian DAI, Xiaojiang WU, Andrew HOADLEY, Lian ZHANG

Frontiers in Energy 2021, Volume 15, Issue 1, Pages 46-67 doi: 10.1007/s11708-020-0807-8

Abstract: In particular, this paper focuses on low-rank coal and biomass that have been receiving increased attentionand slagging indices can only satisfactorily predict the viscosity and slagging propensity of high-rankcoals but cannot predict the slagging propensity and slag viscosity of low-rank coal, and especiallymethod, which can predict/measure the slagging propensity and slag viscosity correctly for all low-rank

Keywords： slag viscosity biomass low-rank coal combustion gasification

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Study on Rank Preservation of the MCDM With Normalizing Formula

Zhang Ling,Zhou Dequn,Li Hongwei,Zhu Peifeng

Strategic Study of CAE 2006, Volume 8, Issue 12, Pages 85-88

Abstract: normalizing formula will result in violations of independence from irrelevant alternatives and lead to rankIn the paper, the two methods that improve the original normalizing formula to erase the rank reversal

Keywords： MCDM decision normalizing violations of independence from irrelevant alternatives rank preservation rank

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An intuitive general rank-based correlation coefficient Research Articles

Divya PANDOVE, Shivani GOEL, Rinkle RANI

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 6, Pages 699-711 doi: 10.1631/FITEE.1601549

Abstract: We propose a predictive metric to calculate correlations between paired values, known as the general rank-basedWe have compared it to Spearman’s rank correlation coefficient.

Keywords： General rank-based correlation coefficient Multivariate analysis Predictive metric Spearman’s rank correlation

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Fuzzy Rank Methodology for Risk Assessment of Environmental Pollution Accidents

Xiong Deqi,Chen Gang,Li Qiong

Strategic Study of CAE 2001, Volume 3, Issue 8, Pages 46-50

Abstract: factories is a multi-criteria and multi-stage process, and is of relativity and fuzziness, the fuzzy rank

Keywords： pollution accidents risk fuzzy assessment rank

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A rank-based multiple-choice secretary algorithm for minimising microgrid operating cost under uncertainties

Frontiers in Energy 2023, Volume 17, Issue 2, Pages 198-210 doi: 10.1007/s11708-023-0874-8

Abstract: To address this challenge, a rank-based multiple-choice secretary algorithm (RMSA) was proposed for microgrid

Keywords： energy management systems demand response scheduling under uncertainty renewable energy sources multiple-choice secretary algorithm

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Low complexity robust adaptive beamforming for general-rank signal model with positive semidefinite constraint Article

Yu-tang ZHU,Yong-bo ZHAO,Jun LIU,Peng-lang SHUI

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 11, Pages 1245-1252 doi: 10.1631/FITEE.1601112

Abstract: We propose a low complexity robust beamforming method for the general-rank signal model, to combat against

Keywords： Beamforming General-rank Low complexity Positive semidefinite (PSD) constraint Model mismatches

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Changes in hourly precipitation may explain the sharp reduction of discharge in the middle reach of the Yellow River after 2000

Lin LUO, Zhongjing WANG

Frontiers of Environmental Science & Engineering 2013, Volume 7, Issue 5, Pages 756-768 doi: 10.1007/s11783-013-0563-7

Abstract: The Hekou-Longmen reach, together with local floods, is the main source area for coarse sedimentations into the Yellow River. When total rainfall slightly increased in the area, discharge dramatically decreased by 40%–70% after the year of 2000, and attracting extensive attention in the context of global climate change. High temporal resolution precipitation (timescales between 1 and 4 h) data from the June to September period from 270 rain gauges over the past three decades was mined in order to help explain the phenomenon. Each rainfall event was classified as light/moderate rain, large rain, heavy rain or rainstorm by the event’s rainfall amount, and further classified as low intensity rain, medium intensity rain and high intensity rain by the event’s rainfall intensity. The Mann-Kendall trend test was applied to detect the presence and significance of monotonic trends, and to find the change points in the mean and variance of the precipitation characteristics series, including the amount, intensity, frequency and duration of each rainfall category. Results show that although the total amount of precipitation has slightly increased, the average rainfall intensity has significantly decreased. The larger change happened in light/moderate rain events and low/medium intensity rain events, and the intensity changes have a great extent occurred around the threshold of Non-Runoff Rainfall regime, which was proposed for the approximate calculation of initial losses. Changes in rainfall distribution between different classes of the Runoff Rainfall regime in the 2000s could lead to 0.9 mm less runoff depth (17.3% of the total reduction) than the 1980–1999 period. The study indicates that changes in hourly precipitation may be responsible for the sharp reduction of discharge.

Keywords： precipitation intensity Mann-Kendall rank statistic spatial and temporal distribution climatic change

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Ensemble unit and AI techniques for prediction of rock strain

Pradeep T; Pijush SAMUI; Navid KARDANI; Panagiotis G ASTERIS

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 7, Pages 858-870 doi: 10.1007/s11709-022-0831-3

Abstract: The behavior of rock masses is influenced by a variety of forces, with measurement of stress and strain playing the most critical roles in assessing deformation. The laboratory test for determining strain at each location within rock samples is expensive and difficult but rock strain data are important for predicting failure of rock material. Many researchers employ AI technology in order to solve these difficulties. AI algorithms such as gradient boosting machine (GBM), support vector regression (SVR), random forest (RF), and group method of data handling (GMDH) are used to efficiently estimate the strain at every point within a rock sample. Additionally, the ensemble unit (EnU) may be utilized to evaluate rock strain. In this study, 3000 experimental data are used for the purpose of prediction. The obtained strain values are then evaluated using various statistical parameters and compared to each other using EnU. Ranking analysis, stress-strain curve, Young’s modulus, Poisson’s ratio, actual vs. predicted curve, error matrix and the Akaike’s information criterion (AIC) values are used for comparing models. The GBM model achieved 98.16% and 99.98% prediction accuracy (in terms of values of R²) in the longitudinal and lateral dimensions, respectively, during the testing phase. The GBM model, based on the experimental data, has the potential to be a new option for engineers to use when assessing rock strain.

Keywords： prediction strain ensemble unit rank analysis error matrix

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Expanding the Scope of Multivariate Regression Approaches in Cross-Omics Research Article

Xiaoxi Hu, Yue Ma, Yakun Xu, Peiyao Zhao, Jun Wang

Engineering 2021, Volume 7, Issue 12, Pages 1725-1731 doi: 10.1016/j.eng.2020.05.028

Abstract: Therefore, in this article, we introduce the reduced rank regression method and its extensions, sparsereduced rank regression and subspace assisted regression with row sparsity, which hold potential to

Keywords： Multivariate regression methods Reduced rank regression Sparsity Dimensionality reduction Variable

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Response of bacterial communities to short-term pyrene exposure in red soil

Jingjing PENG, Hong LI, Jianqiang SU, Qiufang ZHANG, Junpeng RUI, Chao CAI

Frontiers of Environmental Science & Engineering 2013, Volume 7, Issue 4, Pages 559-567 doi: 10.1007/s11783-013-0501-8

Abstract: Pyrene, a representative polycyclic aromatic hydrocarbon (PAH) compound produced mainly from incomplete combustion of fossil fuels, is hazardous to ecosystem health. However, long-term exposure studies did not detect any significant effects of pyrene on soil microorganism. In this study, short-term microcosm experiments were conducted to identify the immediate effect of pyrene on soil bacterial communities. A freshly-collected pristine red soil was spiked with pyrene at 0, 10, 100, 200, and 500 mg·kg and incubated for one day and seven days. The bacterial communities in the incubated soils were analyzed using 16S rRNA sequencing and terminal restriction fragment length polymorphism (T-RFLP) methods. The results revealed high bacterial diversity in both unspiked and pyrene-spiked soils. Only at the highest pyrene-spiking rate of 500 mg·kg , two minor bacteria groups of the identified 14 most abundant bacteria groups were completely suppressed. Short-term exposure to pyrene resulted in dominance of Proteobacteria in soil, followed by Acidobacteria, Firmutes, and Bacteroidetes. Our findings showed that bacterial community structure did respond to the presence of pyrene but recovered rapidly from the perturbation. The intensity of impact and the rate of recovery showed some pyrene dosage-dependent trends. Our results revealed that different levels of pyrene may affect the bacterial community structure by suppressing or selecting certain groups of bacteria. It was also found that the bacterial community was most susceptible to pyrene within one day of the chemical addition.

Keywords： pyrene bacterial communities terminal restriction fragment length polymorphism short-term exposure rank-abundance

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Difficulties and measures for security development of Puguang high-sour gas field

Cao Yaofeng

Strategic Study of CAE 2011, Volume 13, Issue 8, Pages 26-30

Abstract:

Considering the high-risk characteristics of the high-sour gas field development, China Petrochemical Corporation follows the management concepts focusing on safety all the time in the project construction and makes safety the first precondition, primary basis and essential guarantee for the gas field development. By means of strengthening the key links such as standard establishment and implementation, technical innovation, new equipments and new materials R&D and application, system supervision, etc., it overcomes the superior difficulties with high technology and handles the high risks with system control. As a result, it has built the first ultra-deep and high-sour large gas field of China with the scale of over 10 billion cubic meters and the second largest high sour gas purifying plant in the world in 3 years. Meanwhile, it has summarized a complete management mode for developing domestic high-sour gas fields and formed the supporting technologies and specifications for developing high sulfur content gas reservoirs safely and effectively, which has important popularizing and guiding meaning on developing similar gas fields.

Keywords： sour gas rank poison and strong corrosion gas field development security development

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A machine learning approach to query generation in plagiarism source retrieval Article

Lei-lei KONG, Zhi-mao LU, Hao-liang QI, Zhong-yuan HAN

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 10, Pages 1556-1572 doi: 10.1631/FITEE.1601344

Abstract: The proposed method exploits learning to rank to generate queries from the candidates.To solve the essential problem of an absence of training data for learning to rank, the building of training

Keywords： Plagiarism detection Source retrieval Query generation Machine learning Learning to rank