Gongcheng Kexue Yu Jishu/Advanced Engineering Science

Gongcheng Kexue Yu Jishu/Advanced Engineering Science (ISSN: 2096-3246) is a bi-monthly peer-reviewed international Journal. Gongcheng Kexue Yu Jishu/Advanced Engineering Science was originally formed in 1969 and the journal came under scopus by 2017 to now. The journal is published by editorial department of Journal of Sichuan University. We publish every scope of engineering, Mathematics, physics.


Submission Deadline
( Vol 56 , Issue 03 )
03 Apr 2024
Day
Hour
Min
Sec
Publish On
( Vol 56 , Issue 02 )
31 Mar 2024
Scopus Indexed (2024)

Aim and Scope

Gongcheng Kexue Yu Jishu/Advanced Engineering Science (ISSN: 20963246) is a peer-reviewed journal. The journal covers all sort of engineering topic as well as mathematics and physics. the journal's scopes are in the following fields but not limited to:

Agricultural science and engineering Section:

Horticulture, Agriculture, Soil Science, Agronomy, Biology, Economics, Biotechnology, Agricultural chemistry, Soil, development in plants, aromatic plants, subtropical fruits, Green house construction, Growth, Horticultural therapy, Entomology, Medicinal, Weed management in horticultural crops, plant Analysis, Tropical, Food Engineering, Venereal diseases, nutrient management, vegetables, Ophthalmology, Otorhinolaryngology, Internal Medicine, General Surgery, Soil fertility, Plant pathology, Temperate vegetables, Psychiatry, Radiology, Pulmonary Medicine, Dermatology, Organic farming, Production technology of fruits, Apiculture, Plant breeding, Molecular breeding, Recombinant technology, Plant tissue culture, Ornamental horticulture, Nursery techniques, Seed Technology, plantation crops, Food science and processing, cropping system, Agricultural Microbiology, environmental technology, Microbial, Soil and climatic factors, Crop physiology, Plant breeding,

Electrical Engineering and Telecommunication Section:

Electrical Engineering, Telecommunication Engineering, Electro-mechanical System Engineering, Biological Biosystem Engineering, Integrated Engineering, Electronic Engineering, Hardware-software co-design and interfacing, Semiconductor chip, Peripheral equipments, Nanotechnology, Advanced control theories and applications, Machine design and optimization , Turbines micro-turbines, FACTS devices , Insulation systems , Power quality , High voltage engineering, Electrical actuators , Energy optimization , Electric drives , Electrical machines, HVDC transmission, Power electronics.

Computer Science Section :

Software Engineering, Data Security , Computer Vision , Image Processing, Cryptography, Computer Networking, Database system and Management, Data mining, Big Data, Robotics , Parallel and distributed processing , Artificial Intelligence , Natural language processing , Neural Networking, Distributed Systems , Fuzzy logic, Advance programming, Machine learning, Internet & the Web, Information Technology , Computer architecture, Virtual vision and virtual simulations, Operating systems, Cryptosystems and data compression, Security and privacy, Algorithms, Sensors and ad-hoc networks, Graph theory, Pattern/image recognition, Neural networks.

Civil and architectural engineering :

Architectural Drawing, Architectural Style, Architectural Theory, Biomechanics, Building Materials, Coastal Engineering, Construction Engineering, Control Engineering, Earthquake Engineering, Environmental Engineering, Geotechnical Engineering, Materials Engineering, Municipal Or Urban Engineering, Organic Architecture, Sociology of Architecture, Structural Engineering, Surveying, Transportation Engineering.

Mechanical and Materials Engineering :

kinematics and dynamics of rigid bodies, theory of machines and mechanisms, vibration and balancing of machine parts, stability of mechanical systems, mechanics of continuum, strength of materials, fatigue of materials, hydromechanics, aerodynamics, thermodynamics, heat transfer, thermo fluids, nanofluids, energy systems, renewable and alternative energy, engine, fuels, nanomaterial, material synthesis and characterization, principles of the micro-macro transition, elastic behavior, plastic behavior, high-temperature creep, fatigue, fracture, metals, polymers, ceramics, intermetallics.

Chemical Engineering :

Chemical engineering fundamentals, Physical, Theoretical and Computational Chemistry, Chemical engineering educational challenges and development, Chemical reaction engineering, Chemical engineering equipment design and process design, Thermodynamics, Catalysis & reaction engineering, Particulate systems, Rheology, Multifase flows, Interfacial & colloidal phenomena, Transport phenomena in porous/granular media, Membranes and membrane science, Crystallization, distillation, absorption and extraction, Ionic liquids/electrolyte solutions.

Food Engineering :

Food science, Food engineering, Food microbiology, Food packaging, Food preservation, Food technology, Aseptic processing, Food fortification, Food rheology, Dietary supplement, Food safety, Food chemistry. Lizi Jiaohuan Yu Xifu/Ion Exchange and Adsorption Fa yi xue za zhi

Physics Section:

Astrophysics, Atomic and molecular physics, Biophysics, Chemical physics, Civil engineering, Cluster physics, Computational physics, Condensed matter, Cosmology, Device physics, Fluid dynamics, Geophysics, High energy particle physics, Laser, Mechanical engineering, Medical physics, Nanotechnology, Nonlinear science, Nuclear physics, Optics, Photonics, Plasma and fluid physics, Quantum physics, Robotics, Soft matter and polymers.

Mathematics Section:

Actuarial science, Algebra, Algebraic geometry, Analysis and advanced calculus, Approximation theory, Boundry layer theory, Calculus of variations, Combinatorics, Complex analysis, Continuum mechanics, Cryptography, Demography, Differential equations, Differential geometry, Dynamical systems, Econometrics, Fluid mechanics, Functional analysis, Game theory, General topology, Geometry, Graph theory, Group theory, Industrial mathematics, Information theory, Integral transforms and integral equations, Lie algebras, Logic, Magnetohydrodynamics, Mathematical analysis.
Latest Journals
Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-15-06-2022-224

Abstract :

Recommender systems can effectively alleviate the problem of information overload caused by the rapid development of the Internet. However, the occurrence of shilling attacks restricts the healthy development of recommender systems. Therefore, how to detect shilling attacks accurately and efficiently is an important problem in the field of recommender systems security. The existing detection methods usually design hand-crafted detection features based on expert knowledge or automatically learn features from a single perspective using deep learning, then the attack users are identified according to the extracted features by hard classification, resulting in the poor detection performance. By automatically learning features from multiple perspectives and introducing a hesitant fuzzy decision, a novel detection method based on CNN and hesitant fuzzy set was proposed and named CNN-HFS. Firstly, for each user, three behavior matrices were extracted from the perspectives of rating, preference and rating time, respectively. To reduce the influence of data sparse, these matrices were scaled by bicubic interpolation to correspondingly obtain a dense rating matrix, a dense preference matrix and a dense time matrix. Next, each scaling matrix of users was regarded as an image, and three different CNN classifiers were trained based on these scaling matrices in three different views respectively. For each user, three membership degrees to the classifier of attack users were calculated. Finally, a fuzzy hesitant set was introduced to make a comprehensive decision, and the attack users were identified according to the decision results. To validate the effectiveness of the proposed CNN-HFS, the extensive experiments were conducted on the MovieLens 1M and Amazon datasets. The evaluation metrics of precision, recall and F1-measure were used to compare the proposed method with SVM-TIA, CoDetector, CNN-SAD, SDAEs-PCA, CNN-R, CNN-P and CNN-T. The experimental results showed that the proposed method is superior to seven baseline methods in terms of three detection metrics and achieves an excellent detection performance under various attacks.

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Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-15-06-2022-223

Abstract :

For the landslide susceptibility prediction (LSP) based on machine learning (ML) models, the reasonable selection of negative samples has an important influence on the LSP performance. Generally, the main selection methods include randomly selecting from the whole study area or from the specific attribute areas such as low slopes. The negative samples selected by the above methods are often inaccurate or biased, resulting in low accuracy and low reliability of LSP. To solve this problem, the coupling model of ML and information value (IV) method was proposed for LSP. Taking Ruijin City as the study area, the attribute values of the environmental factors were transformed into the IV values of the contribution to the landslide to obtain the very low and low susceptibility areas. The negative samples were randomly selected in the above areas for the training and validation of machine learning models. The new coupling models of IV–SVM and IV–RF were constructed for the LSP of Ruijin. Further, IV–SVM and IV–RF models were compared with the single SVM and RF model with negative samples randomly selected from the whole study area, as well as the low-slope SVM and RF model with negative samples randomly selected from specific attribute areas with a slope less than 2°. Finally, Kappa coefficient (KC) and receiver operating characteristic (ROC) curve were used to verify and compare the modeling results. The AUC values of the ROC curve and KC of IV–SVM and IV–RF models were 0.828, 0.920 and 0.876, 0.988, which were higher than those of single SVM, RF model and low-slope SVM, RF model, respectively. Meanwhile, IV–SVM and IV–RF models have a smaller mean value and larger standard deviation of a susceptibility probability distribution. Results showed that: 1) IV–SVM and IV–RF models had the higher LSP accuracies than those of the single SVM, RF model and low-slope SVM, RF model, respectively; 2) RF model had higher LSP accuracy compared to the SVM model; 3) The coupling model such as IV–RF could address the inaccuracy of negative sample sampling existing in the single model and the shortcomings of the low slope model in the selection of slope interval, thus improving the LSP accuracy. In conclusion, this study provided a new idea for the negative sample sampling method for LSP using ML models

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Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-15-06-2022-222

Abstract :

To verify the applicability of wave theory in studying the free vibration characteristics and impact response of the cable–beam structure, and to preliminarily explore the behaviors of elastic wave propagation through the structure under moving load, the dynamic response function was derived from the transverse vibration differential equation of Timoshenko beam and the longitudinal wave equation of cables. The reverberation-ray matrix was used to obtain the waveform solution of the structural response. Based on the idea of discrete Fourier transform (DFT), the series solution of structural transient response was derived to solve the inverse problem of the traditional reverberation-ray matrix (MRRM). The improved MRRM was verified by experiment and finite element method (FEM). The results showed that at the speed of 30 km/h, the deviation between the theoretical maximum strain and FEM results was 5% and that between theoretical and experimental results was 8%. When the vehicle speed was 40 km/h, the deviation between the theoretical maximum strain and FEM results was 4.0%, which was 9.8% between theoretical and experimental results. Taking the beam-cable system as the research object, the maximum deviation between the first five natural frequencies calculated by improved MRRM and FEM was 0.29%, and the deviation between the first two natural frequencies was 0. The wave response characteristics of the cable-stayed beam under moving load were analyzed and the theoretical results were in good agreement with the FEM results. It could be inferred that the improved MRRM had high reliability in calculating the transient wave response of bridge structure under moving load. Based on the analyses of the frequency domain response, it was found that the flexural waves in the Timoshenko beam under moving load were mainly low-frequency responses whose frequencies were lower than 2 times the fundamental frequency of the structure. Furthermore, the reasonable selection criteria of frequency range were explored in the process of finding the wave response, to further improve the calculation efficiency of MRRM

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Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-15-06-2022-221

Abstract :

To scientifically and reasonably analyze the bending vibration frequency of the new type composite box girder bridge with corrugated steel webs, taking into account the shear deformation effect of corrugated steel webs and the shear lag effect of box girder, the Galerkin method and the Hamilton principle were used to deduce the free vibration control differential equation and natural boundary conditions of the bridge type. According to the natural boundary conditions, the calculation formula of the bending vibration frequency of the new type composite box girder bridge with corrugated steel webs under the influence of shear deformation effect and shear lag effect was solved. The results were compared with the measured results and ANSYS finite element results, and the influencing factors of the bending vibration frequency were analyzed. The results showed that the calculation results of the bending vibration frequency were in good agreement with the measured results and the ANSYS finite element results, which verified the correctness of the derived frequency calculation formula. The bending vibration frequency increased with the increase of the high-span ratio. When it was less than 0.05, the increase of the bending vibration frequency was relatively gentle. When the height-span ratio was greater than 0.05, the increase of the bending vibration frequency was more significant. The bending vibration frequency increased with the increase of the width-span ratio, but the overall increase was not obvious. The frequency increased with the increase of the thickness of the corrugated steel web, and the higher the order, the more significant the increase. The shear lag effect of the box girder had little effect on the bending vibration frequency, and the maximum error of the first 5 orders was only 6.73%. The shear deformation of the corrugated steel webs had a great influence on the bending vibration frequency, and the maximum error of the first five orders was as high as 51.18%

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Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-15-06-2022-220

Abstract :

There are abundant moraine soil sources distributed in the Qinghai–Tibet Plateau of China, with complex historical causes, changeable material structure, and large differences in mechanical properties. Moraine landslide often occurs under the action of rainfall and ice and snow melting. The debris of landslide enters the gully and mixes with water flow, which is very easy to produce the moraine landslide—debris flow—dammed lake disaster chain, which is the key and difficult point of disaster prevention and reduction in the plateau. In recent years, the Sichuan—Tibet railway project and major hydropower development in Tibet have faced a great threat from the moraine landslide—debris flow—dammed lake disaster chain. It is a major national demand to improve the capacity of disaster prevention, reduction and relief. Moraine landslide—debris flow—dammed lake—dam-breaking flood is a chain disaster process of cascade amplification, which involves complex dynamic evolution mechanisms such as landslide initiation, movement behavior transformation, erosion amplification along the process, multi-stage river blocking superposition, and dam break water–sediment coupling. Especially under complex meteorological conditions, there are some problems such as unclear mechanism, inaccurate model, and lack of simulation technology. It is urgent to carry out the research on the complex dynamic mechanism, control theoretical model, and whole process numerical simulation of moraine landslide—debris flow—dammed lake disaster chain process. Combined with the research status at home and abroad, five research contents are further proposed: 1) Evolution of mechanical properties of moraine soil under complex meteorological conditions. 2) Dynamic disaster process and migration model of moraine landslide—debris flow. 3) Formation mechanism and simulation of moraine landslide—debris flow—dammed lake. 4) Mechanism of erosion and outburst of moraine dam and the process of flow channel expansion. 5) Mechanism of water-sediment interaction in the downstream channel and the simulation of flood evolution. Many preliminary explorations and research work have been carried out to preliminarily reveal the migration of moraine landslide debris flow and multi-stage river blocking mechanism, a dam break evolution model that can consider water erosion and intermittent collapse of the broken slope has been built, and the simulation method of moraine landslide—debris flow—dammed lake disaster chain evolution process has been discussed. The results lay a foundation for further understanding of the complex dynamic mechanism of the moraine landslide—debris flow—dammed lake disaster chain process, constructing the control theoretical model and developing the whole process numerical simulation system. And the results are expected to provide a theoretical basis for the mechanism of moraine landslide—debris flow—dammed lake disaster chain and technical support for non-engineering risk reduction and emergency disposal decision-making

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