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CAAI Transactions on Intelligence Technology 2024年第4期9卷 960-972页

作者： Jing Li Dezheng Zhang Yonghong Xie aziguli wulamu Yao Zhang School of Computer and Communication Engineering University of Science and Technology BeijingBeijingChina Beijing Key Laboratory of Knowledge Engineering for Materials Science University of Science and Technology BeijingBeijingChina University of Alberta EdmontonAlbertaCanada

Sentiment analysis is a fine‐grained analysis task that aims to identify the sentiment polarity of a specified *** methods in Chinese sentiment analysis tasks only consider sentiment features from a single pole and scale and thus cannot fully exploit and utilise sentiment feature information,making their performance less than *** resolve the problem,the authors propose a new method,GP‐FMLNet,that integrates both glyph and phonetic information and design a novel feature matrix learning process for phonetic features with which to model words that have the same pinyin information but different glyph *** method solves the problem of misspelling words influencing sentiment polarity prediction ***,the authors iteratively mine character,glyph,and pinyin features from the input comments ***,the authors use soft attention and matrix compound modules to model the phonetic features,which empowers their model to keep on zeroing in on the dynamic‐setting words in various positions and to dispense with the impacts of the deceptive‐setting ***-periments on six public datasets prove that the proposed model fully utilises the glyph and phonetic information and improves on the performance of existing Chinese senti-ment analysis algorithms.

关键词： aspect‐level sentiment analysis deep learning feature extraction glyph and phonetic feature matrix compound learning

Efficient Processing of Skyline Group Queries over a Data Stream

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Tsinghua Science and Technology 2016年第1期21卷 29-39页

作者： Xi Guo Hailing Li aziguli wulamu Yonghong Xie Yajing Fu Beijing Key Laboratory of Knowledge Engineering for Materials Science University of Science and Technology Beijing

In this paper, we study the skyline group problem over a data stream. An object can dominate another object if it is not worse than the other object on all attributes and is better than the other object on at least one attribute. If an object cannot be dominated by any other object, it is a skyline object. The skyline group problem involves finding k-item groups that cannot be dominated by any other k-item group. Existing algorithms designed to find skyline groups can only process static data. However, data changes as a stream with time in many applications,and algorithms should be designed to support skyline group queries on dynamic data. In this paper, we propose new algorithms to find skyline groups over a data stream. We use data structures, namely a hash table, dominance graph, and matrix, to store dominance information and update results incrementally. We conduct experiments on synthetic datasets to evaluate the performance of the proposed algorithms. The experimental results show that our algorithms can efficiently find skyline groups over a data stream.

关键词： skyline skyline group data streams query processing

Three-Phase Unbalance Prediction of Electric Power Based on Hierarchical Temporal Memory

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Computers, Materials & Continua 2020年第8期64卷 987-1004页

作者： Hui Li Cailin Shi Xin Liu aziguli wulamu Alan Yang School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing100083China School of Computer and Communication Engineering University of Science and Technology BeijingBeijing100083China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing100083China Amphenol Assemble Tech HoustonTX 77070USA

The difference in electricity and power usage time leads to an unbalanced current among the three phases in the power *** three-phase unbalanced is closely related to power planning and load *** the unbalance occurs,the safe operation of the electrical equipment will be seriously *** paper proposes a Hierarchical Temporal Memory(HTM)-based three-phase unbalance prediction model consisted by the encoder for binary coding,the spatial pooler for frequency pattern learning,the temporal pooler for pattern sequence learning,and the sparse distributed representations classifier for unbalance *** the feasibility of spatial-temporal streaming data analysis,we adopted this brain-liked neural network to a real-time prediction for power *** applied the model in five cities(Tangshan,Langfang,Qinhuangdao,Chengde,Zhangjiakou)of north *** experimented with the proposed model and Long Short-term Memory(LSTM)model and analyzed the predict results and real *** results show that the predictions conform to the reality;compared to LSTM,the HTM-based prediction model shows enhanced accuracy and *** prediction model could serve for the overload warning and the load planning to provide high-quality power grid operation.

关键词： Three-phase unbalance power load prediction model hierarchical temporal memory

A Heterogeneous Ensemble of Extreme Learning Machines with Correntropy and Negative Correlation

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Tsinghua Science and Technology 2017年第6期22卷 691-701页

作者： Adnan O.M.Abuassba Yao Zhang Xiong Luo Dezheng Zhang wulamu aziguli School of Computer and Communication Engineering University of Science and Technology Beijing(USTB)Beijing 100083China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing 100083China School of Engineering New York UniversityBrooklynNY 11201USA

The Extreme Learning Machine（ELM） is an effective learning algorithm for a Single-Layer Feedforward Network（SLFN）. It performs well in managing some problems due to its fast learning speed. However, in practical applications, its performance might be affected by the noise in the training data. To tackle the noise issue, we propose a novel heterogeneous ensemble of ELMs in this article. Specifically, the correntropy is used to achieve insensitive performance to outliers, while implementing Negative Correlation Learning（NCL） to enhance diversity among the ensemble. The proposed Heterogeneous Ensemble of ELMs（HE2 LM） for classification has different ELM algorithms including the Regularized ELM（RELM）, the Kernel ELM（KELM）, and the L2-norm-optimized ELM（ELML2）. The ensemble is constructed by training a randomly selected ELM classifier on a subset of the training data selected through random resampling. Then, the class label of unseen data is predicted using a maximum weighted sum approach. After splitting the training data into subsets, the proposed HE2 LM is tested through classification and regression tasks on real-world benchmark datasets and synthetic datasets. Hence, the simulation results show that compared with other algorithms, our proposed method can achieve higher prediction accuracy, better generalization, and less sensitivity to outliers.

关键词： Extreme Learning Machine(ELM) ensemble classification correntropy negative correlation

Ore Image Segmentation Method Based on U-Net and Watershed

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Computers, Materials & Continua 2020年第10期65卷 563-578页

作者： Hui Li Chengwei Pan Ziyi Chen aziguli wulamu Alan Yang School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing100083China School of Computer and Communication Engineering University of Science and Technology BeijingBeijing100083China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing100083China Amphenol AssembleTech Houston77070USA

Ore image segmentation is a key step in an ore grain size analysis based on image *** traditional segmentation methods do not deal with ore textures and shadows in ore images well Those methods often suffer from under-segmentation and *** this article,in order to solve the problem,an ore image segmentation method based on U-Net is *** adjust the structure of U-Net to speed up the processing,and we modify the loss function to enhance the generalization of the *** the collection of the ore image,we design the annotation standard and train the network with the annotated ***,the marked watershed algorithm is used to segment the adhesion *** experimental results show that the proposed method has the characteristics of fast speed,strong robustness and high *** has great practical value to the actual ore grain statistical task.

关键词： Image segmentation ore grain size U-Net watershed algorithm

Degradation modeling research of biodegradable tissue engineering scaffold

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Degradation modeling research of biodegradable tissue engine...

Modeling and Simulation of degradation for Biodegradable PolymerBased on Cellular Automata(CA)

第八届中国功能材料及其应用学术会议

作者： ZHANG Tao-hong XU Shou-gang Zhang De-zheng aziguli wulamu School of Computer and Communication Engineering University of Science and Technology Beijing(USTB) Beijing Key Laboratory of Knowledge Engineering for Materials Science

Although the degradation modeling of tissue engineering scaffold is in its initial step,it can direct the design,optimization of scaffold and help the application in medical case of *** paper analyzes the modeling methods and gives the speciality of every model which is put forward by researchers in China and abroad about the degradation of tissue engineering *** models are divided into micro scale,macro scale and two scale models based on the modeling *** recent research is belonging to single scale *** researchers abroad probed to two scale *** future model is prospected in multi scale coupling macro,micro,and meta-macro model.

关键词： biodegradable polymer tissue engineering scaffold degradation degradation modeling

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Modeling and Simulation of degradation for Biodegradable Pol...

第八届中国功能材料及其应用学术会议

作者： ZHANG Tao-hong XU Shou-gang XIN Rui-wu ZHANG De-zheng aziguli wulamu School of Computer and Communication Engineering University of Science and Technology Beijing(USTB) Beijing Key Laboratory of Knowledge Engineering for Materials Science

In this article a model based on cellular automata(CA)isproposed to simulate the degradation for biodegradable *** rule of this model is constructed based onthe hydrolysis reaction,oligomer diffusion equations and the relationship between intensity and number average molecular weight of the ***,polymer DLPLA plate corresponding to this CA model was carried *** simulation shows the middle hollow result which is accordance with the experiment *** molecular in the degradation process has good fit with the experiment *** proves that the model in this article is right and can provide numerical lead for the designsof biodegradable polymerdevices.

关键词： Cellular Automata(CA) Computer Simulation Biodegradable Polymer degradation

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KDD*SS的知识库结构设计与实现

系统工程与电子技术 2005年第4期27卷 757-760页

作者：谢永红杨炳儒吾拉木.阿兹古丽北京科技大学信息工程学院北京100083

针对知识发现系统的不同应用场合,实现了一套基于各类关系型数据库的通用型知识发现工具的数据预处理子系统。该系统通过ODBC可访问各类关系型数据库,并运用数据库系统的视图机制、数据仓库的主题思想以及语言场理论等思想方法,在用户... 详细信息

针对知识发现系统的不同应用场合,实现了一套基于各类关系型数据库的通用型知识发现工具的数据预处理子系统。该系统通过ODBC可访问各类关系型数据库,并运用数据库系统的视图机制、数据仓库的主题思想以及语言场理论等思想方法,在用户没有建立数据仓库的情况下,可利用此系统自主建立灵活的知识发现系统。给出了该系统的具体功能和实现方法。

关键词：知识发现数据挖掘数据预处理主题管理

Robust Cultivated Land Extraction Using Encoder-Decoder

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Journal of New Media 2020年第4期2卷 149-155页

作者： aziguli wulamu Jingyue Sang Dezheng Zhang and Zuxian Shi Department of Computer School of Computer and Communication EngineeringUniversity of Science and Technology Beijing(USTB)Beijing100083China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing100083China 不详

Cultivated land extraction is essential for sustainable development and *** this paper,the network we propose is based on the encoder-decoder structure,which extracts the semantic segmentation neural network of cultivated land from satellite images and uses it for agricultural automation *** encoder consists of two part:the first is the modified Xception,it can used as the feature extraction network,and the second is the atrous convolution,it can used to expand the receptive field and the context information to extract richer feature *** decoder part uses the conventional upsampling operation to restore the original *** addition,we use the combination of BCE and Loves-hinge as a loss function to optimize the Intersection over Union(IoU).Experimental results show that the proposed network structure can solve the problem of cultivated land extraction in Yinchuan City.

关键词： Semantic segmentation encoder-decoder cultivated land extraction atrous convolution

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卷烟制造工业互联网平台建设与应用

计算机集成制造系统 2020年第12期26卷 3427-3434页

作者：李奇颖赵阳阿孜古丽·吾拉木张健车常通杨剑锋孔维熙龙小昂北京易华录信息技术股份有限公司北京100043 北京科技大学计算机与通信工程学院北京100083 北京航空航天大学自动化科学与电气工程学院北京100191 中国烟草总公司北京100045 红云红河烟草(集团)有限责任公司曲靖卷烟厂云南曲靖655001 深圳华龙讯达信息技术股份有限公司广东深圳518000

在分析国内外工业互联网及平台战略政策和研究发展现状的基础上,结合烟草行业卷烟制造实际应用需求和已有的自动化和信息化现状,建设了以信息物理系统(CPS)、工业物联网、生产制造仿真系统为核心的卷烟制造工业互联网平台,从而打造数据... 详细信息

在分析国内外工业互联网及平台战略政策和研究发展现状的基础上,结合烟草行业卷烟制造实际应用需求和已有的自动化和信息化现状,建设了以信息物理系统(CPS)、工业物联网、生产制造仿真系统为核心的卷烟制造工业互联网平台,从而打造数据采集、数据建模、数据分析、虚拟制造、产品和设备全生命周期管理服务能力,实现了生产前虚拟仿真,进行生产预演,提升资源配置能力;实现了生产中实时仿真,进行生产监控诊断,提升了制造管控能力;实现了生产后回溯仿真,进行生产评估优化,提升了制造创新能力;同时,实现了产品和设备全生命周期管理,提高了设备使用效率和扩展产品价值空间。卷烟制造工业互联网平台的应用在提质增效和降耗节能方面取得了显著成效。

关键词：卷烟制造生产制造仿真系统信息物理系统工业物联网虚拟仿真