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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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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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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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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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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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Exploring self-organization and self-adaption for smart manufacturing complex networks

Frontiers of Engineering Management 2023, Volume 10, Issue 2,   Pages 206-222 doi: 10.1007/s42524-022-0225-1

Abstract: In this context, this paper investigates the mechanisms and methodology of self-organization and self-adaptionSubsequently, analytical target cascading is used to formulate the processes of self-organizing optimalconfiguration and self-adaptive collaborative control for multilevel key manufacturing resources whilework potentially enables managers and practitioners to implement active perception, active response, self-organization, and self-adaption solutions in discrete manufacturing enterprises.

Keywords： cyber–physical systems     Industrial Internet of Things     smart manufacturing complex networks     self-organizationand self-adaption     analytical target cascading     collaborative optimization    

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Forget less, count better: a domain-incremental self-distillation learning benchmark for lifelong crowd Research Article

Jiaqi GAO, Jingqi LI, Hongming SHAN, Yanyun QU, James Z. WANG, Fei-Yue WANG, Junping ZHANG

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 2,   Pages 187-202 doi: 10.1631/FITEE.2200380

Abstract: A robust and practical system has to be capable of continuously learning with the newly incoming domainSpecifically, we propose a self-distillation learning framework as a benchmark (forget less, count better

Keywords： Crowd counting     Knowledge distillation     Lifelong learning    

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Interactive medical image segmentation with self-adaptive confidence calibration

沈楚云,李文浩,徐琪森,胡斌,金博,蔡海滨,朱凤平,李郁欣,王祥丰

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 9,   Pages 1332-1348 doi: 10.1631/FITEE.2200299

Abstract: Interactive medical image segmentation based on human-in-the-loop machine learning is a novel paradigmwe propose an interactive segmentation framework, called interactive MEdical image segmentation with self-adaptiveConfidence CAlibration (MECCA), which combines action-based confidence learning and multi-agent reinforcementlearning.

Keywords： Medical image segmentation     Interactive segmentation     Multi-agent reinforcement learning     Confidence learning     Semi-supervised learning    

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Emerging trends in self-healable nanomaterials for triboelectric nanogenerators: A comprehensive review

Frontiers in Energy   Pages 727-750 doi: 10.1007/s11708-023-0896-2

Abstract: A thorough analysis of triboelectric nanogenerators (TENGs) that make use of self-healable nanomaterialsTENGs, on the other hand, provide unique opportunities for future self-powered systems and might encourageExamining the many approaches used to improve nanogenerators by employing materials with shape memory and self-healableAdditionally, the cost-effectiveness, social acceptability, and regulatory implications of self-healing

Keywords： triboelectric nanogenerator (TENG)     self-healable nanomaterials     self-powered devices     energy    

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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

The Design of a Valve Positioner System Based on ARM Microcontroller

Wu Aiguo,Wang Lishi

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

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

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

Exploring self-organization and self-adaption for smart manufacturing complex networks

Journal Article

Forget less, count better: a domain-incremental self-distillation learning benchmark for lifelong crowd

Jiaqi GAO, Jingqi LI, Hongming SHAN, Yanyun QU, James Z. WANG, Fei-Yue WANG, Junping ZHANG

Journal Article

Interactive medical image segmentation with self-adaptive confidence calibration

沈楚云,李文浩,徐琪森,胡斌,金博,蔡海滨,朱凤平,李郁欣,王祥丰

Journal Article

Emerging trends in self-healable nanomaterials for triboelectric nanogenerators: A comprehensive review

Journal Article