Deep Learning for Power System Applications
Case Studies Linking Artificial Intelligence and Power Systems
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Fan** Li
Artificial Intelligence
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Article
Open AccessMethodology and real-world applications of dynamic uncertain causality graph for clinical diagnosis with explainability and invariance
AI-aided clinical diagnosis is desired in medical care. Existing deep learning models lack explainability and mainly focus on image analysis. The recently developed Dynamic Uncertain Causality Graph (DUCG) app...
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Article
Feature reused network: a fast segmentation network model for strip steel surfaces defects based on feature reused
The strip steel is a common metallic material with a wide range of applications in various industries. However, the issue of surface defects that possess high concealment and low discrimination, which arises d...
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Article
A novel forecasting model based on the raised ordered pair fuzzy time series and fuzzy implication
In fuzzy time series (FTS) based forecasting models, FTS is utilized to depict the characteristic of time series. In the constructed FTS of the existing models, each moment consists of a fuzzy set to reflect t...
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Article
Open AccessA Feature Selection Method Based on Feature-Label Correlation Information and Self-Adaptive MOPSO
Feature selection can be seen as a multi-objective task, where the goal is to select a subset of features that exhibit minimal correlation among themselves while maximizing their correlation with the target la...
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Article
MGCRL: Multi-view graph convolution and multi-agent reinforcement learning for dialogue state tracking
Dialogue state tracking (DST) is a significant part of prevalent task-oriented dialogue systems, which monitor the user’s goals based on current and previous dialogues for effective dialogue management. Howeve...
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Article
Deep feature network with multi-scale fusion for highly congested crowd counting
In this paper, we propose a deep feature network with multi-scale fusion (DFNet) for addressing the problem of crowd counting in highly congested noisy scenes. DFNet contains three modules: feature encoder, fe...
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Article
Memory augmented echo state network for time series prediction
Echo state networks (ESNs), a special class of recurrent neural networks (RNNs), have attracted extensive attention in time series prediction problems. Nevertheless, the memory ability of ESNs is contradictory...
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Book
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Book
Fuzzy Rule-Based Inference
Advances and Applications in Reasoning with Approximate Knowledge Interpolation
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Chapter and Conference Paper
Asymptomatic Carriers are Associated with Shorter Negative Conversion Time in Children with Omicron Infections
Objective: Among the Omicron carriers, asymptomatic ones should be paid close attention to due to their silence in clinical symptoms and uncertainty in secondary transmission. The clinical characteristics asso...
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Chapter
Summary and Future Works
This chapter gives a brief summary of the research works from Chaps. 2, 3, 4 and al...
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Chapter
Prospectives of Further Developments and Applications of Approximate Knowledge Interpolation
This final chapter concludes the book. Firstly, it provides a summary of the topics presented in the preceding chapters, including an emphasis on the recent advances in approximate knowledge interpolative reas...
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Chapter and Conference Paper
Robust Self-contact Detection Based on Keypoint Condition and ControlNet-Based Augmentation
Existing self-contact detection methods have difficulty detecting dense per-vertex self-contact. Dataset collection for existing self-contact detection methods is costly and inefficient, as it requires differe...
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Chapter and Conference Paper
Design of Push Algorithm for Individualized Course Content of College Public Art Education Online Education
In order to improve the adaptability of online education personalized course push resources and user demand resources, and reduce the push time, a new push method is designed for online education personalized ...
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Chapter and Conference Paper
Embedded Computing Course Design for Internet of Things and Smart Things Applications
With the rapid advancement of IoT technology, IoT education has emerged as a new challenge in university education. A course named “Smart Hardware and Intelligent Systems” is designed to target for undergradua...
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Chapter
Introduction: A Brief History of Deep Learning and Its Applications in Power Systems
This chapter gives a brief introduction to the history of deep learning and the associated concepts. One step further, various deep learning applications in the area of power systems are also discussed to prov...
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Chapter and Conference Paper
Exploring the Linguistic Model to Operate on Architectural Façade Illumination Design
Designers utilize the compositions to express their feelings and thoughts. However, it is difficult to have corresponding command of design theory for people in different fields. For architects, it is not comm...
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Chapter
Practical Integrated Weighted Approximate Reasoning
Pattern-matching-based approximate reasoning methods (e.g. CRI) can be effective and efficient when applicable, while FRI methods work well when facing incomplete knowledge bases. To maximise the benefits of b...
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Chapter and Conference Paper
Building a Credit Evaluation Model for C2C E-commerce Websites Under the Guidance of Decision Trees
Recently, C2C online shop** has gained popularity among consumers. However, with technological advancements, the virtualization, anonymization, and shortening of transaction time in online trading have led t...
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Chapter and Conference Paper
A New Approach for Ontology Generation from Relational Data Design Patterns
Knowledge graphs can effectively manage domain knowledge such as entities, properties, relations and events. Recent years have witnessed quite a few successful AI applications with the help of knowledge graphs...
