Sustainable energy development in the Chinese countryside

Wang, X. H.; Liu, Lili; Zhang, X. C.

doi:10.1179/014426005x50760

Cited by 4 publications

(4 citation statements)

References 7 publications

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“… Year Ref. Object of Study 1 2005 [ 11 ] This is sustainable energy development in the Chinese countryside and discusses the main problems of sustainable energy development during different periods. 2 2006 [ 12 ] This studies regional and agricultural policy in Spain from 1985 to 2006.…”

Section: Conceptual Frameworkmentioning

confidence: 99%

Sustainable Development in Rural Territories within the Last Decade: A Review of the State of the Art

Roldán¹,

Giraldo²,

López-Santana³

2023

Heliyon

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Section: Conceptual Frameworkmentioning

confidence: 99%

Sustainable Development in Rural Territories within the Last Decade: A Review of the State of the Art

Roldán¹,

Giraldo²,

López-Santana³

2023

Heliyon

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“…BP neural network is used in the prediction of compressive strength of long standing concrete after exposure to high temperature in literature [3], the predicted values reached a good agreement with the test results. The compressive strength of concrete under salt erosion is predicted by using the BP neural network, the error between predicted values and experimental values is less in literature [6]. Shear strength of reinforced concrete beam is predicted by using the BP neural network, comparing with the experimental values, the prediction accuracy is higher than the calculated value in literature [7].…”

Section: Introductionmentioning

confidence: 95%

Prediction of Hybrid Fiber Reinforced Concrete Strength on Base of RBF & BP

Zhao

Wang

et al. 2014

AMR

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The complex nonlinear problem exists between the factors which influence the strength of hybrid fiber reinforced concrete. The nonlinear relationship between input variables as the factors and output variables as the strength can be obtained artificial neural network which have the feature of self-adapting, self-studying and nonlinear mapping. RBF and BP neural network models are established in MATLAB in this paper based on experimental values. Compressive strength and flexural strength of hybrid fiber reinforced concrete are predicted respectively and comparing with the measured values, predicted values are analyzed. The results show that the predicted values based on RBF tally with the experimental values, and the strength prediction ability of RBF is higher than BP neural network. The needs of engineering can be meet by this method with accurate prediction ability, a new method for the study of hybrid fiber reinforced concrete strength is provided.

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“…Using linear elastic mechanical model [2], in order to clearly reflect the steel reinforced lightweight aggregate concrete beams stress, strain development situation, this is the model of steel and lightweight aggregate concrete separation [3][4]. Unit type is the eight node hexahedron unit, the numerical simulation analysis of beam grid figure1, the material parameters such as table1.…”

Section: Numerical Simulationmentioning

confidence: 99%

Numerical Simulation on Beating Capacity of Steel Reinforced Light Aggregate Concrete Beam

Zhang¹,

Zhang²

2013

AMM

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For a better analysis of the deformation of the steelreinforced light aggregate concrete member, adopt asymmetric loading mode,carry on numerical simulation of bearing capacity of steel reinforced lightaggregate concrete beams. The simulation results show that the: In theasymmetric loads, longitudinal reinforcement of the bottom of the beam both ends of the constrained position, due tothe presence of constraints, make it tensile stress,in the 250mmposition is tensile stress minimum, compressive stress correspondingly larger.In the central beam downward bending deformation, this part of the lower edgeof the beam longitudinal reinforcement tensile stress.

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Sustainable energy development in the Chinese countryside

Cited by 4 publications

References 7 publications

Sustainable Development in Rural Territories within the Last Decade: A Review of the State of the Art

Sustainable Development in Rural Territories within the Last Decade: A Review of the State of the Art

Prediction of Hybrid Fiber Reinforced Concrete Strength on Base of RBF & BP

Numerical Simulation on Beating Capacity of Steel Reinforced Light Aggregate Concrete Beam

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Sustainable energy development in the Chinese countryside

Cited by 4 publications

References 7 publications

Sustainable Development in Rural Territories within the Last Decade: A Review of the State of the Art

Sustainable Development in Rural Territories within the Last Decade: A Review of the State of the Art

Prediction of Hybrid Fiber Reinforced Concrete Strength on Base of RBF &amp; BP

Numerical Simulation on Beating Capacity of Steel Reinforced Light Aggregate Concrete Beam

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Prediction of Hybrid Fiber Reinforced Concrete Strength on Base of RBF & BP