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Short-Term Building Load Forecast Based on Patch Learning with Long Short-Term Memory Network and Support Vector Regression 1

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2nd International Conference on Neural Computing for Advanced Applications, NCAA 2021

作者： Dan, Zhaohui Wang, Bo Fan, Huijin Liu, Lei Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Artificial Intelligence and Automation School Huazhong University of Science and Technology Wuhan430074 China

ISBN: (数字)9789811651885

ISBN: (纸本)9789811651878

This paper proposes a novel short-term building load forecasting approach under the framework of patch learning, a novel data-driven model that aggregates a global model and several patch models to further reduce forecasting errors. A PL-LSTM-SVR model is hereby employed to address such a time-series based forecasting problem, where the long short-term memory network is considered as the global model and the support vector regression is selected as the patch model. To obtain satisfying performances, an infinity norm measurement is selected to evaluate load forecasting errors and identify patch locations. Furthermore, a genetic algorithm with elitist preservation strategy is introduced for hyperparameter tuning. The performances of the proposed PL-LSTM-SVR model are tested and verified on two different data sets, and compared with four advanced building load forecasting models on several common metrics. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Long short-term memory

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Prostate surgery path planning based on simplified delay-PCNN

Prostate surgery path planning based on simplified delay-PCN...

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2011 IEEE International conference on intelligent Computation and Bio-Medical Instrumentation, ICBMI 2011

作者： Li, He Zhang, Xuming Hou, Wenguang Ding, Mingyue Life School of Science and Technology Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9780769546230

This paper presents an algorithm to find the shortest path in 3D(three-dimensional) prostate surgery planning. Using a simplified delay pulse coupled neural network(S-DPCNN) model, a shortest path can be drawn automatically from the target position to the puncture point. Compared to the traditional pulse coupled neural network(PCNN), S-DPCNN needs much fewer neurons and therefore decreases complexity of computation. Experiments on computer simulations show the validity of this method. © 2011 IEEE.

关键词： Motion planning

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An approach with nested partition for resource-constrained project scheduling problem

An approach with nested partition for resource-constrained p...

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19th International Conference on Industrial Engineering and Engineering Management: Assistive Technology of Industrial Engineering

作者： Liu, Zhen-Yuan Yu, Wen-Min Institute of Systems Engineering Huazhong University of Science and Technology Wuhan China Key Laboratory of Education Ministry for Image Processing and Intelligent Control Wuhan China

ISBN: (纸本)9783642383908

A time-based nested partition (NP) approach is proposed to solve resource-constrained project scheduling problem (RCPSP) in this paper. In iteration, one activity is selected as the base point of which the finish time interval calculated by CPM is divided into two parts to form two subregions on the basis of the promising region of the last iteration. Then sampling is taken in both subregions and the surrounding region to determine the promising region and aggregate the other as the surrounding region of this iteration so that whether the backtracking or the moving operation being performed is determined. Double justification is also performed in iteration to improve the results. The results of numerical tests on PSPLIB show the effectiveness and time-efficient of the proposed NP method. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Scheduling

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Geometric active contour model and its application to carotid plaque detection

Geometric active contour model and its application to caroti...

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2011 IEEE International conference on intelligent Computation and Bio-Medical Instrumentation, ICBMI 2011

作者： Cheng, Jieyu Ding, Mingyue Zhang, Xuming Life School of Science and Technology Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan China

ISBN: (纸本)9780769546230

This paper gives an overview of three different geometric active contour models with the focus on the application to carotid plaque detection from cross-sectional ultrasound images of the carotid artery. On one hand, basic principles of these geometric active contour models are presented. On the other hand, performance of these models are tested on 16 images and compared with the manual delineations. © 2011 IEEE.

关键词： Ultrasonic applications

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Knowledge-Data Fusion Based Source-Free Semi-Supervised Domain Adaptation for Seizure Subtype Classification

Knowledge-Data Fusion Based Source-Free Semi-Supervised Doma...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Peng, Ruimin An, Jiayu Wu, Dongrui School of Artificial Intelligence and Automation Huazhong University of Science and Technology Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control Wuhan430074 China

ISBN: (纸本)9781665410205

Electroencephalogram (EEG)-based seizure sub-type classification enhances clinical diagnosis efficiency. Source-free semi-supervised domain adaptation (SF-SSDA), which transfers a pre-trained model to a new dataset with no source data and limited labeled target data, can be used for privacy-preserving seizure subtype classification. This paper considers two challenges in SF-SSDA for EEG-based seizure subtype classification: 1) How to effectively fuse both raw EEG data and expert knowledge in classifier design? 2) How to align the source and target domain distributions for SF-SSDA? We propose a Knowledge-Data Fusion based SF-SSDA approach, KDF-MutuaISHOT, for EEG-based seizure subtype classification. In source model training, KDF uses Jensen-Shannon Diver-gence to facilitate mutual learning between a feature-driven Decision Tree-based model and a data-driven Transformer-based model. To adapt KDF to a new target dataset, an SF-SSDA algorithm, MutualSHOT, is developed, which features a consistency-based pseudo-label selection strategy. Experiments on the public TUSZ and CHSZ datasets demonstrated that KDF-MutualSHOT outperformed other supervised and source-free domain adaptation approaches in cross-subject seizure subtype classification. © 2024 IEEE.

关键词： Self-supervised learning

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A protocol for structured illumination microscopy with minimal reconstruction artifacts

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Biophysics Reports 2019年第2期5卷 80-90页

作者： Junchao Fan Xiaoshuai Huang Liuju Li Shan Tan Liangyi Chen Key Laboratory of Image Processing and Intelligent Control of Ministry of Education of China School of Automation Huazhong University of Science and Technology State Key Laboratory of Membrane Biology Beijing Key Laboratory of Cardiometabolic Molecular MedicineInstitute of Molecular Medicine Peking University

The imaging rate of structured illumination microscopy(SIM) reached 188 Hz recently. As the exposure time decreases, the camera detects fewer virtual photons, while the noise level remains the same. As a result, the signal-to-noise ratio(SNR) decreases sharply. Furthermore, the SNR decreases further because of photobleaching and phototoxicity. This decreased quality of SIM raw data may lead to surprising artifacts with various causes, which may confuse a new user of SIM microscopy. We summarize three significant possible sources of severe artifacts in reconstructed super-resolution(SR)images. Ultrafast motion of a biological sample or an uneven illumination pattern is the most difficult to be identified. The estimated parameter could also be incorrect, leading to artifact of regular ***, reconstruction with the Wiener method generates stochastic artifacts due to the amplification of noise during the deconvolution process. To deal with these problems, we have established a protocol to reconstruct ultrafast SIM raw data obtained in low SNR conditions. First, we checked the quality of the raw data with the image J plugin SIMcheck before reconstruction. Then, a modified parameter estimation method was used to improve the precision of the parameters. Finally, an iterative algorithm was used for SIM reconstruction under low signal-to-noise ratio conditions. This procedure effectively suppressed the artifacts in the super-resolution images reconstructed from raw data of low signal-to-noise ratio.

关键词： Ultrafast SIM Low signal-to-noise ratio Reconstruction

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A REVIEW ON ARTERY WALL SEGMENTATION TECHNIQUES AND INTIMA-MEDIA THICKNESS MEASUREMENT FOR CAROTID ULTRASOUND imageS

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Journal of Innovative Optical Health Sciences 2012年第1期5卷 75-84页

作者： XIN YANG WANJI HE KAITONG LI JIAOYING JIN XUMING ZHANG MING YUCHI MINGYUE DING State Key Laboratory for Multi-Spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence(IPRAI)Huazhong University of Science and Technology Wuhan 430074HubeiChina Image Processing and Intelligence Control Key Laboratory of Education Ministry of China School of Life Science and Technology Huazhong University of Science and Technology Wuhan 430074HubeiChina

Stroke and heart attack,which could be led by a kind of cerebrovascular and cardiovascular disease named as atherosclerosis,would seriously cause human morbidity and *** is important for the early stage diagnosis and monitoring medical intervention of the *** stenosis is a classical atherosclerotic lesion with vessel wall narrowing down and accumulating plaques *** carotid artery of intima-media thickness(IMT)is a key indicator to the *** the development of computer assisted diagnosis technology,the imaging techniques,segmentation algorithms,measurement methods,and evaluation tools have made considerable *** imaging,being real-time,economic,reliable,and safe,now seems to become a standard in vascular assessment methodology especially for the measurement of *** review firstly attempts to discuss the clinical relevance of measurements in clinical practice at first,and then followed by the challenges that one has to face when approaching the segmentation of ultrasound ***,the commonly used methods for the IMT segmentation and measurement are ***,discussion and evaluation of different segmentation techniques are *** overview of summary and future perspectives is given finally.

关键词： Ultrasound(US)images carotid artery intima-media thickness(IMT) atherosclerosis image segmentation computer assisted diagnosis(CAD)

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Super Twisting control of Passive Gait Training Exoskeleton Driven by Pneumatic Muscles 30

Super Twisting Control of Passive Gait Training Exoskeleton ...

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30th International Symposium on Micro-NanoMechatronics and Human Science, MHS 2019

作者： Zhang, Mengshi Huang, Jian Cao, Yu Zhang, Hai-Tao Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781728126746

Pneumatic Muscles (PMs) - driven exoskeleton has a promising prospect in the field of rehabilitation and assistance, because of the PMs intrinsic features of compliance and high force-to-weight ratio. However, the precise control of PMs-driven exoskeleton still remains a challenging problem due to the hysteresis, time-varying parameters of PMs and complexity of the mechanism. To solve this problem, this paper presents a super twisting controller (STC), essentially a second-order sliding mode control, to realize the human gait tracking control of lower limb exoskeleton. As a result, the disturbances and uncertainties of the system can be handled, and the chattering caused by the traditional sliding mode control (SMC) could be eliminated. The stability of the closed-loop system is ensured according to the Lyapunov theorem. In addition, we conduct experiments in real exoskeleton system and the results illustrate the validity of the super twisting algorithm. Pneumatic Muscles (PMs) - driven exoskeleton has a promising prospect in the field of rehabilitation and assistance, because of the PMs' intrinsic features of compliance and high force-to-weight ratio. However, the precise control of PMs-driven exoskeleton still remains a challenging problem due to the hysteresis, time-varying parameters of PMs and complexity of the mechanism. To solve this problem, this paper presents a super twisting controller (STC), essentially a second-order sliding mode control, to realize the human gait tracking control of lower limb exoskeleton. As a result, the disturbances and uncertainties of the system can be handled, and the chattering caused by the traditional sliding mode control (SMC) could be eliminated. The stability of the closed-loop system is ensured according to the Lyapunov theorem. In addition, we conduct experiments in real exoskeleton system and the results illustrate the validity of the super twisting algorithm.. © 2019 IEEE.

关键词： Sliding mode control

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An Improved Reinforcement Learning for Security-Constrained Economic Dispatch of Battery Energy Storage in Microgrids 1

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2nd International Conference on Neural Computing for Advanced Applications, NCAA 2021

作者： Zha, Zhongyi Wang, Bo Fan, Huijin Liu, Lei Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Artificial Intelligence and Automation School Huazhong University of Science and Technology Wuhan430074 China

ISBN: (数字)9789811651885

ISBN: (纸本)9789811651878

Battery energy storage systems are widely used in microgrids integrated with volatile energy resources for their ability in peak load shifting. Security constrained economic dispatch over the system’s lifecycle is a constrained multi-period stochastic optimization problem, which is intractable. We propose an improved actor-critic-based reinforcement learning combined with a protection layer security control method for this issue, where the distributional critic net is applied to estimate the expected total reward value of a period more accurately, and the policy net with a mask action layer is used to make secure and real-time decision. Additionally, we propose a protection layer to assist the policy net as a secondary control to prevent the unsafe state of microgrids due to the trial-and-error learning of reinforcement learning. Numerical test results show the proposed algorithm can perform better than the conventional economic dispatch and other reinforcement learning algorithms while guaranteeing safe operation. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Renewable energy resources

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Enhancing Resilience of Microgrid-Integrated Power Systems in Disaster Events Using Reinforcement Learning 1

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Chinese intelligent Automation Conference, CIAC 2023

作者： Zha, Zhongyi Wang, Bo Liu, Lei Fan, Huijin Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Artificial Intelligence and Automation School Huazhong University of Science and Technology Wuhan430074 China

ISBN: (数字)9789819961870

ISBN: (纸本)9789819961863

Enhancing the resilience of power systems has become increasingly important to mitigate the negative impact of risk attacks. Integrating microgrids, which are small-scale power grids that can operate independently or in conjunction with the main grid, has emerged as an effective energy source for emergency situations and can avoid power outages. Typhoons, which are inevitable and relatively easy to predict risk attacks, have become one of the contexts to examine power system resilience. In this paper, we propose a reinforcement learning algorithm that combines graph theory knowledge to make decisions for optimizing power system resilience with microgrids under the Typhoon event. The algorithm effectively utilizes graph theory knowledge and reduces the number of decisions required in the optimization process. Numerical experimental results show that compared to traditional methods, the reinforcement learning algorithm can more effectively respond to typhoon changes, achieve flexible economic control, and enhance the resilience of power systems with microgrids. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Numerical methods

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