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User Purchase Intention Prediction Based on Improved Deep Forest

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 661-677页

作者： yifan zhang Qiancheng Yu Lisi zhang School of Computer Science and Engineering North Minzu UniversityYinchuan750030China Laboratory of Graphics and Images of the State Ethnic Affairs Commission North Minzu UniversityYinchuan750030China

Widely used deep neural networks currently face limitations in achieving optimal performance for purchase intention prediction due to constraints on data volume and hyperparameter *** address this issue,based on the deep forest algorithm and further integrating evolutionary ensemble learning methods,this paper proposes a novel Deep Adaptive Evolutionary Ensemble(DAEE)*** model introduces model diversity into the cascade layer,allowing it to adaptively adjust its structure to accommodate complex and evolving purchasing behavior ***,this paper optimizes the methods of obtaining feature vectors,enhancement vectors,and prediction results within the deep forest algorithm to enhance the model’s predictive *** demonstrate that the improved deep forest model not only possesses higher robustness but also shows an increase of 5.02%in AUC value compared to the baseline ***,its training runtime speed is 6 times faster than that of deep models,and compared to other improved models,its accuracy has been enhanced by 0.9%.

关键词： Purchase prediction deep forest differential evolution algorithm evolutionary ensemble learning model selection

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Light(Science & Applications) 2024年第2期13卷 333-346页

作者： yifan Sun Qian Li Ling-Jun Kong Xiangdong zhang Key Laboratory of advanced optoelectronic quantum architecture and measurements of Ministry of Education Beijing Key Laboratory of Nanophotonics&Ultrafine Optoelectronic SystemsSchool of PhysicsBeijing Institute of Technology100081BeijingChina

Compared with electrical neural networks,optical neural networks(ONNs)have the potentials to break the limit of the bandwidth and reduce the consumption of energy,and therefore draw much attention in recent *** far,several types of ONNs have been ***,the current ONNs cannot realize the acceleration as powerful as that indicated by the models like quantum neural *** to construct and realize an ONN with the quantum speedup is a huge ***,we propose theoretically and demonstrate experimentally a new type of optical convolutional neural network by introducing the optical *** is called the correlated optical convolutional neural network(COCNN).We show that the COCNN can exhibit“quantum speedup”in the training *** character is verified from the two *** is the direct illustration of the faster convergence by comparing the loss function curves of the COCNN with that of the traditional convolutional neural network(CNN).Such a result is compatible with the training performance of the recently proposed quantum convolutional neural network(QCNN).The other is the demonstration of the COCNN’s capability to perform the QCNN phase recognition circuit,validating the connection between the COCNN and the ***,we take the COCNN analog to the 3-qubit QCNN phase recognition circuit as an example and perform an experiment to show the soundness and the feasibility of *** results perfectly match the theoretical *** proposal opens up a new avenue for realizing the ONNs with the quantum speedup,which will benefit the information processing in the era of big data.

关键词： process quantum convolution

Advances in MET tyrosine kinase inhibitors in gastric cancer

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Cancer Biology & Medicine 2024年第6期21卷 484-498页

作者： yifan zhang Lin Shen Zhi Peng Key Laboratory of Carcinogenesis and Translational Research(Ministry of Education) Department of Gastrointestinal OncologyPeking University Cancer Hospital&InstituteBeijing 100142China State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers Beijing Key Laboratory of Carcinogenesis and Translational ResearchDepartment of Gastrointestinal OncologyPeking University Cancer Hospital&InstituteBeijing 100142China

Gastric cancer is among the most frequently occurring cancers and a leading cause of cancer-related deaths *** gastric cancer is highly heterogenous and comprised of different subtypes with distinct molecular and clinical characteristics,the management of gastric cancer calls for better-defined,biomarker-guided,molecular-based treatment *** is a receptor tyrosine kinase mediating important physiologic processes,such as embryogenesis,tissue regeneration,and wound ***,mounting evidence suggests that aberrant MET pathway activation contributes to tumour proliferation and metastasis in multiple cancer types,including gastric cancer,and is associated with poor patient *** such,MET-targeting therapies are being actively developed and promising progress has been demonstrated,especially with MET tyrosine kinase *** review aims to briefly introduce the role of MET alterations in gastric cancer and summarize in detail the current progress of MET tyrosine kinase inhibitors in this disease area with a focus on savolitinib,tepotinib,capmatinib,and *** on current knowledge,this review further discusses existing challenges in MET alterations testing,possible resistance mechanisms to MET inhibitors,and future directions of MET-targeting therapies.

关键词： Gastric cancer MET alterations MET tyrosine kinase inhibitors savolitinib MET testing

A Web-like Three-dimensional Binder for Silicon Anode in Lithium-ion Batteries

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Energy & Environmental Materials 2024年第1期7卷 21-27页

作者： Liyuan Li Tao Li yifan Sha Baozeng Ren Lan zhang Suojiang zhang CAS Key Laboratory of Green Process and Engineering Beijing Key Laboratory of Ionic Liquids Clean ProcessState Key Laboratory of Multiphase Complex SystemsInstitute of Process EngineeringChinese Academy of SciencesBeijing 100190China School of Chemical Engineering Zhengzhou UniversityZhengzhou 450001China Langfang Green Industrial Technology Center Langfang 065001China Henan Key Laboratory of Energy Storage Materials and Processes Zhengzhou Institute of Emerging Industrial TechnologyZhengzhou 450003China

Si anode is of paramount importance for advanced energy-dense lithium-ion batteries(LIBs).However,the large volume change as well as stress generates during its lithiation-delithiation process poses a great challenge to the long-term cycling and hindering its *** this work,a composite binder is prepared with a soft component,guar gum(GG),and a rigid linear polymer,anionic polyacrylamide(APAM).Rich hydroxy,carboxyl,and amide groups on the polymer chains not only enable intermolecular crosslinking to form a web-like binder,A2G1,but also realize strong chemical binding as well as physical encapsulating to Si *** resultant electrode shows limited thickness change of merely 9%on lithiation and almost recovers its original thickness on *** demonstrates high reversible capacity of 2104.3 mAh g^(-1)after 100 cycles at a current density of 1800 mA g^(-1),and in constant capacity(1000 mAh g^(-1))test,it also shows a long life of 392 ***,this soft-hard combining web-like binder illustrates its great potential in the future applications.

关键词： anionic polyacrylamide lithium-ion batteries Si anode thickness change web-like binder

High-resolution tsunami hazard assessment for the Guangdong-Hong Kong-Macao Greater Bay Area based on a non-hydrostatic tsunami model

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Science China Earth Sciences 2024年第7期67卷 2326-2351页

作者： yifan ZHU Chao AN Houyun YU Wei zhang Xiaofei CHEN Key Laboratory of Hydrodynamics(Ministry of Education) School of Ocean and Civil EngineeringShanghai Jiao Tong UniversityShanghai 200240China Department of Earth and Space Sciences Southern University of Science and Technology Shenzhen 518055China

The Guangdong-Hong Kong-Macao Greater Bay Area(GBA)is threatened by potential tsunami hazards from the Littoral Fault Zone(LFZ)and the Manila subduction zone(MSZ),and may suffer huge damage because of its dense population,concentrated infrastructure,and low-lying *** tsunami studies for the GBA made simple assumptions on the mechanisms of LFZ earthquakes,and used coarse bathymetry data in tsunami simulation,which limited the prediction of detailed tsunami hazard *** this paper,we develop a parallel dispersive tsunami model PCOMCOT to efficiently simulate dispersive,nonlinear,and breaking tsunami *** also construct large-scale and high-resolution bathymetry models for the GBA by correcting and integrating various data *** rupture simulation is performed for the LFZ to obtain a more reliable earthquake source *** propose several representative earthquake scenarios for the LFZ and MSZ,and use PCOMCOT to calculate the resulting tsunami waves,currents,and inundation in the *** results indicate that if an M_(w)7.5 oblique-slip earthquake occurs in the LFZ off the Pearl River Estuary(PRE),the subsequent tsunami will primarily impact Hong Kong,causing maximum positive and negative waves of around 1 m and -2 m,respectively,along with slightly destructive currents(≥1.5 m/s).An M_(w)9.0 MSZ megathrust earthquake can lead to widespread inundation with>1 m depth on the outlying islands of Macao and in the urban areas of Hong Kong around the Victoria ***,it will also cause catastrophic tsunami currents along the narrow waterways in Hong Kong and Macao,and the spatial distribution of strong currents(≥3 m/s)shows a considerable discrepancy from the areas of serious ***,more attention should be paid to the potential impacts of tsunami currents on the GBA.

关键词： Tsunami hazards Inundation Tsunami currents Non-hydrostatic model Guangdong-Hong Kong-Macao Greater Bay Area

Anomaly Detection Algorithm of Power System Based on Graph Structure and Anomaly Attention

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Computers, Materials & Continua 2024年第4期79卷 493-507页

作者： yifan Gao Jieming zhang Zhanchen Chen Xianchao Chen Zhaoqing Power Supply Bureau of Guangdong Power Grid Co. Ltd.Zhaoqing526060China

In this paper, we propose a novel anomaly detection method for data centers based on a combination of graphstructure and abnormal attention mechanism. The method leverages the sensor monitoring data from targetpower substations to construct multidimensional time series. These time series are subsequently transformed intograph structures, and corresponding adjacency matrices are obtained. By incorporating the adjacency matricesand additional weights associated with the graph structure, an aggregation matrix is derived. The aggregationmatrix is then fed into a pre-trained graph convolutional neural network (GCN) to extract graph structure ***, both themultidimensional time series segments and the graph structure features are inputted into a pretrainedanomaly detectionmodel, resulting in corresponding anomaly detection results that help identify abnormaldata. The anomaly detection model consists of a multi-level encoder-decoder module, wherein each level includesa transformer encoder and decoder based on correlation differences. The attention module in the encoding layeradopts an abnormal attention module with a dual-branch structure. Experimental results demonstrate that ourproposed method significantly improves the accuracy and stability of anomaly detection.

关键词： Anomaly detection transformer graph structure

Constitutive model of viscoelastic dynamic damage for the material of gas obturator in modular-charge howitzer

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Defence Technology（防务技术） 2024年第9期39卷 203-216页

作者： Zhonggang Li Longmiao Chen yifan Li Yufeng Jia Quan zhang School of Mechanical Engineering Nanjing University of Science and TechnologyNanjing 210094China Technology Center Shanxi North Machine-building Co.Ltd.Taiyuan 030009China Research and Development Department Kelong New Material Technology Co.Ltd.Xianyang 712000China

In order to investigate the mechanical response behavior of the gas obturator of the breech mechanism,made of polychloroprene rubber(PCR), uniaxial compression experiments were carried out by using a universal testing machine and a split Hopkinson pressure bar(SHPB), obtaining stress-strain responses at different temperatures and strain rates. The results revealed that, in comparison to other polymers, the gas obturator material exhibited inconspicuous strain softening and hardening effects;meanwhile, the mechanical response was more affected by the strain rate than by temperature. Subsequently, a succinct viscoelastic damage constitutive model was developed based on the ZWT model, including ten undetermined parameters, formulated with incorporating three parallel components to capture the viscoelastic response at high strain rate and further enhanced by integrating a three-parameter Weibull function to describe the damage. Compared to the ZWT model, the modified model could effectively describe the mechanical response behavior of the gas obturator material at high strain rates. This research laid a theoretical foundation for further investigation into the influence of chamber sealing issues on artillery firing.

关键词： Breech mechanism Gas obturator Polychloroprene rubber Constitutive model Strain rate Damage

Microwave-assisted pyrolysis of plastics for aviation oil production:energy and economic analyses

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Frontiers of Chemical Science and Engineering 2024年第7期18卷 141-153页

作者： Sichen Fan yifan Liu Yaning zhang Wenke Zhao Chunbao Xu School of Energy Science and Engineering Harbin Institute of TechnologyHarbin 150001China School of Energy and Environment City University of Hong KongHong Kong SARChina

Microwave-assisted pyrolysis is an effective method for recycling plastic wastes into oils that can be used for aviation fuels. In this study, energy and economic analyses of aviation oil production from microwave-assisted pyrolysis of polystyrene were performed. The total energy efficiency, recovered energy efficiency, unitary cost, unitary energy economic cost, relative cost difference, and energy economic factor were detailed. And the effects of microwave power, pyrolysis temperature, microwave absorbent loading, and microwave absorbent type on these parameters were covered. It was found that pyrolysis temperature has the most significant effect on the unitary cost and unitary energy economic cost of aviation oil, and-microwave absorbent type has a significant influence on energy economic factor during the whole microwave-assisted pyrolysis process. The optimum reaction conditions at the tonnage system for pyrolysis of 1 t polystyrene were microwave power of 650 W, pyrolysis temperature of 460 ℃, and silicon carbide (microwave absorbent) at a loading of 2 t (twice than feedstock loading). At these optimal conditions, the total energy efficiency, recovered energy efficiency, unitary cost, unitary energy economic cost, relative cost difference, and energy economic factor were 62.78%, 96.51%, 3.21 × 10^(4) yuan·t^(-1), 779 yuan·GJ^(-1), 1.49, and 71.02%, respectively.

关键词： energy analysis economic analysis microwave-assisted pyrolysis polystyrene aviation oil

Feature Matching via Topology-Aware Graph Interaction Model

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 113-130页

作者： yifan Lu Jiayi Ma Xiaoguang Mei Jun Huang Xiao-Ping zhang the Electronic Information School Wuhan UniversityWuhan 430072China IEEE Tsinghua Berkeley Shenzhen Institute Shenzhen 518071China the Department of Electrical Computer and Biomedical EngineeringToronto Metropolitan UniversityToronto ON M5B 2K3Canada

Feature matching plays a key role in computer vision. However, due to the limitations of the descriptors, the putative matches are inevitably contaminated by massive *** paper attempts to tackle the outlier filtering problem from two aspects. First, a robust and efficient graph interaction model,is proposed, with the assumption that matches are correlated with each other rather than independently distributed. To this end, we construct a graph based on the local relationships of matches and formulate the outlier filtering task as a binary labeling energy minimization problem, where the pairwise term encodes the interaction between matches. We further show that this formulation can be solved globally by graph cut algorithm. Our new formulation always improves the performance of previous localitybased method without noticeable deterioration in processing time,adding a few milliseconds. Second, to construct a better graph structure, a robust and geometrically meaningful topology-aware relationship is developed to capture the topology relationship between matches. The two components in sum lead to topology interaction matching(TIM), an effective and efficient method for outlier filtering. Extensive experiments on several large and diverse datasets for multiple vision tasks including general feature matching, as well as relative pose estimation, homography and fundamental matrix estimation, loop-closure detection, and multi-modal image matching, demonstrate that our TIM is more competitive than current state-of-the-art methods, in terms of generality, efficiency, and effectiveness. The source code is publicly available at http://***/yifanLu2000/TIM.

关键词： Feature matching graph cut outlier filtering topology preserving