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Multi-color space threshold segmentation and self-learning k-NN algorithm for surge test EUT status

Jian HUANG,Gui-xiong LIU

Frontiers of Mechanical Engineering 2016, Volume 11, Issue 3,   Pages 311-315 doi: 10.1007/s11465-016-0376-z

Abstract: A multi-color space threshold segmentation and self-learning k-nearest neighbor algorithm

Keywords： multi-color space     k-nearest neighbor algorithm (k-NN)     self-learning     surge test    

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Research on An On-line Tracking Self-learning Algorithm for Fuzzy Basis Function Neural Network

Xu Feiyun,Zhong Binglin,Huang Ren

Strategic Study of CAE 2007, Volume 9, Issue 11,   Pages 48-53

Abstract:

An on-line tracking self-learning algorithm for fuzzy basis function

Keywords： fuzzy basis function     self-learning     fault diagnosis    

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A combination weighting model based on iMOEA/D-DE Research Article

Mingtao DONG, Jianhua CHENG, Lin ZHAO,hbdmt@hrbeu.edu.cn,chengjianhua@hrbeu.edu.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 4,   Pages 604-616 doi: 10.1631/FITEE.2000545

Abstract: This paper proposes a (CW) model based on i (i.‍e., improved multiobjective evolutionary algorithm based on decomposition with differential evolution) with the aim to accurately compute the weight of evaluation methods. Multi-expert weight considers only subjective weights, leading to poor objectivity. To overcome this shortcoming, a multiobjective optimization model of CW based on improved is proposed while considering the uncertainty of combination coefficients. An improved mutation operator is introduced to improve the convergence speed, and thus better optimization results are obtained. Meanwhile, an adaptive mutation constant and crossover probability constant with are proposed to improve the robustness of . Since the existing weight evaluation approaches cannot evaluate weights separately, a new weight evaluation approach based on is presented. Taking the evaluation method of integrated navigation systems as an example, certain experiments are carried out. It is proved that the proposed algorithm is effective and has excellent performance.

Keywords： Combination weighting     MOEA/D-DE     Game theory     Self-learning ability     Relative entropy    

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The Design of a Valve Positioner System Based on ARM Microcontroller

Wu Aiguo,Wang Lishi

Strategic Study of CAE 2005, Volume 7, Issue 4,   Pages 69-73

Abstract: On the other hand, the design of control method with intelligent integral and self-learning fuzzy controller

Keywords： ARM     controller     CANbus     intelligent integral     self-learning fuzzy controller    

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Self-propelled automatic chassis of Lunokhod-1: History of creation in episodes

Mikhail MALENKOV

Frontiers of Mechanical Engineering 2016, Volume 11, Issue 1,   Pages 60-86 doi: 10.1007/s11465-016-0370-5

Abstract:

This report reviews the most important episodes in the history of designing the self-propelled automatic

Keywords： moon rover     self-propelled chassis     propulsion     wheel     suspension     soil properties     cross-country ability    

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Unknown fault detection for EGT multi-temperature signals based on self-supervised feature learning and

Frontiers in Energy 2023, Volume 17, Issue 4,   Pages 527-544 doi: 10.1007/s11708-023-0880-x

Abstract: Data-based methods of supervised learning have gained popularity because of available Big Data and computingHowever, the common paradigm of the loss function in supervised learning requires large amounts of labeledTherefore, a fault detection method based on self-supervised feature learning was proposed to addressFirst, self-supervised learning was employed to extract features under various working conditions onlyThe self-supervised representation learning uses a sequence-based Triplet Loss.

Keywords： fault detection     unary classification     self-supervised representation learning     multivariate nonlinear    

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Optimization of machine learning models for predicting the compressive strength of fiber-reinforced self-compacting

Frontiers of Structural and Civil Engineering 2023, Volume 17, Issue 2,   Pages 284-305 doi: 10.1007/s11709-022-0901-6

Abstract: Fiber-reinforced self-compacting concrete (FRSCC) is a typical construction material, and its compressiveIn the machine learning (ML) approach to estimating the CS of FRSCC, the current research gaps include

Keywords： compressive strength     self-compacting concrete     artificial neural network     decision tree     CatBoost    

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Assessment of different machine learning techniques in predicting the compressive strength of self-compacting

Van Quan TRAN; Hai-Van Thi MAI; Thuy-Anh NGUYEN; Hai-Bang LY

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 7,   Pages 928-945 doi: 10.1007/s11709-022-0837-x

Abstract: The compressive strength of self-compacting concrete (SCC) needs to be determined during the constructionstrength of SCC (CS of SCC) can be successfully predicted from mix design and curing age by a machine learning

Keywords： compressive strength     self-compacting concrete     machine learning techniques     particle swarm optimization    

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Multiple input self-organizing-map ResNet model for optimization of petroleum refinery conversion units

Frontiers of Chemical Science and Engineering 2023, Volume 17, Issue 6,   Pages 759-771 doi: 10.1007/s11705-022-2269-5

Abstract: This work introduces a deep-learning network, i.e., multi-input self-organizing-map ResNet (MISR), forThe model is comprised of self-organizing-map and the neural network parts.The self-organizing-map part maps the input data into multiple two-dimensional planes and sends themstructure predicts more accurately the product yields and properties than the previously introduced self-organizing-map

Keywords： hydrocracking     convolutional neural networks     self-organizing map     deep learning     data-driven optimization    

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A hybrid machine learning model to estimate self-compacting concrete compressive strength

Hai-Bang LY; Thuy-Anh NGUYEN; Binh Thai PHAM; May Huu NGUYEN

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 8,   Pages 990-1002 doi: 10.1007/s11709-022-0864-7

Abstract: wolf optimizer (GWO) and artificial neural network (ANN) to predict the compressive strength (CS) of self-compacting

Keywords： artificial neural network     grey wolf optimize algorithm     compressive strength     self-compacting concrete    

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Innovation self, Technology Learning and Elevation of Industry Competence — Case of Taiwan IC Industry

Lu Rui,Sheng Zhaohan

Strategic Study of CAE 2007, Volume 9, Issue 8,   Pages 35-39

Abstract: the paper analyzes its technology innovation and its elevation of industry competence by technology learningand innovation-self.

Keywords： technology learning     innovation-self     industry competence     IC industry    

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reduces IgE binding ability of allergenic egg white proteins

Sen LI, Marina OFFENGENDEN, Michael G. GÄNZLE, Jianping WU

Frontiers of Agricultural Science and Engineering 2018, Volume 5, Issue 3,   Pages 373-381 doi: 10.15302/J-FASE-2018210

Abstract: of this study was to investigate the effect of Aspergillus oryzae cultivation on IgE binding abilityAdding mycelium of A. oryzae ATCC 1011 and 16868 substantially reduced the IgE binding abilityTherefore, the reduction of IgE binding ability of egg white proteins during A. oryzae treatment

Keywords： Aspergillus oryzae     egg allergy     egg white proteins     IgE-binding ability     ovomucoid    

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Filtration ability of hollow fiber membrane for production of magnesium ammonium phosphate crystals by

H. Watamura, H. Marukawa, I. Hirasawa

Frontiers of Chemical Science and Engineering 2013, Volume 7, Issue 1,   Pages 55-59 doi: 10.1007/s11705-013-1312-y

Abstract: Relationship between magnesium ammonium phosphate (MAP) crystal properties and the filtration ability

Keywords： membrane separation     crystallization     MAP    

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A numerical wave model with weak nonlinearity and its application ability analysis

Liu Zhongbo,Tang Jun

Strategic Study of CAE 2010, Volume 12, Issue 9,   Pages 96-100

Abstract:

Based on the extended Boussinesq equation with weak nonlinearity, 2-D numerical model was established in nonstaggered grids by the finite difference method. The nonstaggered grids were used with the first-order spatial derivatives being discretized by the fourth-order and the second-order terms discertized by the second-order. For the time derivatives, a composite fourth-order accurate Adams-Bashforth Moulton scheme was used. Numerical simulation was done upon one-dimension and two-dimension wave propagations problem, and through the comparisons of numerical results with the related experimental data, the application of the extended Boussinesq equations were investigated.

Keywords： numerical model     application ability     wave    

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Self-supervised graph learning with target-adaptive masking for session-based recommendation Research Article

Yitong WANG, Fei CAI, Zhiqiang PAN, Chengyu SONG,wangyitong20@nudt.edu.cn,caifei08@nudt.edu.cn,panzhiqiang@nudt.edu.cn,songchengyu@nudt.edu.cn

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 1,   Pages 73-87 doi: 10.1631/FITEE.2200137

Abstract: To tackle the above issues, we propose a self-supervised graph learning with (SGL-TM) method.Specifically, we first construct a global graph based on all involved sessions and subsequently capture the self-supervisedFinally, we combine the main supervised component with the auxiliary self-supervision module to obtain

Keywords： Session-based recommendation     Self-supervised learning     Graph neural networks     Target-adaptive masking    

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Title Author Date Type Operation

Multi-color space threshold segmentation and self-learning k-NN algorithm for surge test EUT status

Jian HUANG,Gui-xiong LIU

Journal Article

Research on An On-line Tracking Self-learning Algorithm for Fuzzy Basis Function Neural Network

Xu Feiyun,Zhong Binglin,Huang Ren

Journal Article

A combination weighting model based on iMOEA/D-DE

Mingtao DONG, Jianhua CHENG, Lin ZHAO,hbdmt@hrbeu.edu.cn,chengjianhua@hrbeu.edu.cn

Journal Article

The Design of a Valve Positioner System Based on ARM Microcontroller

Wu Aiguo,Wang Lishi

Journal Article

Self-propelled automatic chassis of Lunokhod-1: History of creation in episodes

Mikhail MALENKOV

Journal Article

Unknown fault detection for EGT multi-temperature signals based on self-supervised feature learning and

Journal Article

Optimization of machine learning models for predicting the compressive strength of fiber-reinforced self-compacting

Journal Article

Assessment of different machine learning techniques in predicting the compressive strength of self-compacting

Van Quan TRAN; Hai-Van Thi MAI; Thuy-Anh NGUYEN; Hai-Bang LY

Journal Article

Multiple input self-organizing-map ResNet model for optimization of petroleum refinery conversion units

Journal Article

A hybrid machine learning model to estimate self-compacting concrete compressive strength

Hai-Bang LY; Thuy-Anh NGUYEN; Binh Thai PHAM; May Huu NGUYEN

Journal Article

Innovation self, Technology Learning and Elevation of Industry Competence — Case of Taiwan IC Industry

Lu Rui,Sheng Zhaohan

Journal Article

reduces IgE binding ability of allergenic egg white proteins

Sen LI, Marina OFFENGENDEN, Michael G. GÄNZLE, Jianping WU

Journal Article

Filtration ability of hollow fiber membrane for production of magnesium ammonium phosphate crystals by

H. Watamura, H. Marukawa, I. Hirasawa

Journal Article

A numerical wave model with weak nonlinearity and its application ability analysis

Liu Zhongbo,Tang Jun

Journal Article

Self-supervised graph learning with target-adaptive masking for session-based recommendation

Yitong WANG, Fei CAI, Zhiqiang PAN, Chengyu SONG,wangyitong20@nudt.edu.cn,caifei08@nudt.edu.cn,panzhiqiang@nudt.edu.cn,songchengyu@nudt.edu.cn

Journal Article