Lifeng Wu

Nanchang Institute of Technology

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i-10 index

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Co-Authors

Sifeng Liu

Nanjing University of Aeronautics and Astronautics

Yan Chen

Hebei University of Engineering

Yingjie Yang

De Montfort University

Yinao Wang

Eastern Cooperative Oncology Group

Lianyi Liu

Nanjing University of Aeronautics and Astronautics

Shuli Yan

Nanjing University of Information Science and Technology

Jianlong Guo

Nanjing Forestry University

Ligen Yao

Hebei University of Engineering

Zhicun Xu

Nanjing University of Aeronautics and Astronautics

Zhengran Qiao

Shanxi University

Cooperative Institutions

Hebei University of Engineering

Nanjing University of Aeronautics and Astronautics

Chinese Academy of Sciences

University of Chinese Academy of Sciences

Handan College

University of Electronic Science and Technology of China

China University of Mining and Technology

Nanjing University

Tsinghua University

Nanjing University of Information Science and Technology

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Research Field

Multi-parameter Equipment Cost Estimation Based on New Information Principle Principal Component Regression

Zhongguo guanli kexue (2012)

Lifeng Wu

One key issue is how to choose appropriate cost drive factors to model equipment cost.In this paper,the new information principle of grey system is applied to model principal component analysis,which can find the data law of new information fully.Different types of avionics equipment cost is estimated.The results prove that the new method can improve the forecast performance compared with traditional back- propagation neural network method and support vector machine method.

Component (thermodynamics)

Principal component regression

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Citations (2)

Forecasting air quality considering the socio-economic development in Xingtai

Sustainable Cities and Society (2020)

Kaihe Shi Lifeng Wu

10.1016/j.scs.2020.102337

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Citations (33)

A novel fractional Bessel grey system model optimized by Salp Swarm Algorithm for renewable energy generation forecasting in developed countries of Europe and North America

Computational and Applied Mathematics (2025)

Xin Ma Hong Yuan Minda Ma Lifeng Wu

10.1007/s40314-024-03013-w

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Using fractional GM(1,1) model to predict maintenance cost of weapon system

Shili Fang Lifeng Wu Yu Liang Zhigeng Fang

In order to improve the prediction performance for maintenance cost of weapon system, grey system model with the fractional order accumulation (FGM(1,1)) is used to predict the maintenance cost of weapon system with small sample. FGM(1,1) yielded the lower MAPE in the in-sample model and the much lower MAPE in the out-of-sample model, which means that FGM(1,1) can predict the memory process. FGM(1,1) can predict the maintenance cost of other weapon system.

Sample (material)

Weapon system

10.1109/gsis.2013.6714760

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Citations (13)

Main Factors Influencing the Color Quality During Color Matching Process

China Plastics (2008)

Lifeng Wu

The factors influencing color quality of plastic products were analyzed using a computerized color-measuring instrument.It showed that the basic color of resin,the average molecular weight and melting point of polyethylene wax,crystal form of the organic pigment,and surface morphology of pig- ment particles have significant effects on the color quality of final products.

Color difference

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Urban natural gas consumption forecasting by novel wavelet-kernelized grey system model

Engineering Applications of Artificial Intelligence (2023)

Xin Ma Hongfang Lu Minda Ma Lifeng Wu Yubin Cai

Kernel (algebra)

Hyperparameter Optimization

10.1016/j.engappai.2022.105773

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Citations (25)

Effect of LDPE with High MI on the Rheological Properties of Color Masterbatch

Gōsei jushi (2011)

Lifeng Wu

The melt index and rheological properties of color masterbatch were investigated with three different kinds of LDPE which MI was 20,40,80 g/10 min.The relationship of tinting strength and dispersibility of color masterbatch between melt index and rheology was analysed.The result showed that the processability of color masterbatch was better when adpoted higher MI among three kinds of high MI LDPE.And tinting strength and dispersibility of color masterbatch also changed with the content of high MI LDPE'change,but then decreased.Among the three LDPE,the MI value of 40 g/10 min prepared LDPE masterbatch'tinting strength and dispersibility was good.And the content was 42 % ,it was the best.

Masterbatch

Low-density polyethylene

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Using grey Lotka-Volterra model to analyze the relationship between the gross domestic products and the foreign direct investment of Ningbo city

Lifeng Wu Sifeng Liu

The relationship between the economic growth and foreign direct investment (FDI) has been the concern of the researchers. The grey Lotka-Volterra model is employed to analyze the relationship between the gross domestic products (GDP) and FDI in Ningbo from 1999 to 2007. The discrete Lotka-Volterra model is applied to predict the GDP and the FDI in Ningbo respectively. The results demonstrate that there is mutually beneficial relationship between the GDP and the FDI in Ningbo in the long run, and the FDI of current year restricts economic development.

Investment

10.1109/gsis.2013.6714796

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Citations (3)

Using fractional order accumulation to reduce errors from inverse accumulated generating operator of grey model

Soft Computing (2014)

Lifeng Wu Sifeng Liu Ligen Yao Ruiting Xu Lei Xun-ping

Operator (biology)

10.1007/s00500-014-1268-y

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Citations (68)

An optimized grey model for predicting non-renewable energy consumption in China

Heliyon (2023)

Jianlong Guo Lifeng Wu Yali Mu

The large amount of the non-renewable energy consumption in China brings certain challenges to the realization of carbon neutrality. This paper proposes a new grey model to predict the consumption of non-renewable energy in China. Based on the traditional grey model, the proposed model introduces two parameters to adjust the weight of information. Simultaneously, the intelligent optimization algorithm determines the optimal parameters. Three cases verify the feasibility of the model. The forecast results show that the amount of oil and natural gas consumption will continue to grow at a faster rate. By 2026, the amount of oil consumption will exceed 37 EJ (EJ) and natural gas consumption will exceed 22 EJ. Compared to 2021, oil consumption is up nearly 24%, and natural gas consumption is up more than 60%. While the consumption of coal will maintain a small up rate and gradually be leveled off.

Consumption

Oil consumption

Realization (probability)

Carbon neutrality

10.1016/j.heliyon.2023.e17037

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Citations (7)