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Distributed flow controller for mobile ad-hoc networks

Distributed flow controller for mobile ad-hoc networks

引用

International symposium on Applied computational intelligence and Informatics ( SACI)

作者： Gheorghe Mülec Radu Vasiu Flaviu Frigura-Iliasa Faculty of Electronics and Telecommunications Engineering Politehnica University of Timisoara Romania Faculty of Electrical and Power Engineering Politehnica University of Timisoara Romania

A mobile ad-hoc network (MANET) is a self-configuring, self-organized, and infrastructureless network of mobile stations, connected by radio links. The challenge to ensure network's operation means to continuously maintain updated information about the network's topology, the characteristics of the radio links and security at all levels. Due to the decentralized nature of the network, this is quite difficult. Distributed coordination and control of MANET has always been a challenge for network designers. This paper presents a proposal for a distributed flow controller, a new approach regarding the network architecture for MANET. From the perspective of the current approaches, the entire network has to be treated as a whole, from the point of view of the management, control and data plane. Our proposed approach, based on the paradigm of SDN (Software Design Network), implies a clear separation between the data plane and the control plane. This separation leads to greater flexibility on the control network, to the possibility of dynamic reconfiguration, and to the improvement of its security.

关键词： Mobile computing Mobile communication Mobile ad hoc networks Network topology Security Process control

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Early Forest Fire Recognition Method Based on C-GhostNet Network 5

Early Forest Fire Recognition Method Based on C-GhostNet Net...

引用

5th International symposium on Autonomous Systems, ISAS 2022

作者： Li, Mengna Zhang, Youmin Mu, Lingxia Xin, Jing Yu, Ziquan Jiao, Shangbin Liu, Han Xie, Guo Yi, Yingmin Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Shaanxi Xi'an710048 China Concordia University Industrial and Aerospace Engineering Department of Mechanical MontrealQCH3G 1M8 Canada Nanjing University of Aeronautics and Astronautics College of Automation Engineering Nanjing211106 China Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an Shaanxi 710048 China

ISBN: (纸本)9781665487085

Early forest fire image recognition plays an important role in timely fire fighting. This paper proposes an early forest fire recognition method based on C-GhostNet network. The C-GhostNet network is an improved version of GhostNet, which mainly consists of a series of c-ghost bottlenecks, each c-ghost bottleneck mainly consists of two c-ghost modules. Through the concat operation and channel shuffle, the c-ghost module establishes the relationship between the input data and the output features generated by the original ghost module, so that GhostNet network has the ability to capture contextual features. The experimental results show that the C-GhostNet network achieves better recognition performance than GhostNet without introducing additional computational load, and the running speed reaches about 20FPS, which basically realizes real-time recognition. In addition, like GhostN et, the C-GhostNet network is also a lightweight network. © 2022 ieee.

关键词： Image recognition

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Intelligent Speed Adaptation Using a Self-Organizing Neuro-Fuzzy controller

Intelligent Speed Adaptation Using a Self-Organizing Neuro-F...

引用

ieee symposium on Intelligent Vehicle

作者： David Partouche Michel Pasquier Anne Spalanzani Institut National Polytechnique de Grenoble Nanyang Technological University Singapore Pierre-Mendès France University Grenoble France

The need to increase road safety is a major concern, with millions of road users and pedestrians being killed in traffic accidents each year. The Centre for computational intelligence (C 2 i) at NTU has developed an intelligent driving system based on hybrid fuzzy neural networks, which is able to park autonomously, drive on highways, and take some decisions such as lane changing, car following, and overtaking. This paper presents a new approach to autonomously adapt the speed of a vehicle by learning from a human driver and using anticipation. The architecture of the system is a specific fuzzy neural network realized at C2i: the Generic Self Organizing Fuzzy Neural Network using the Yager inference scheme (GenSoFNN(Yager)). Experiments have been conducted in simulation to test the longitudinal control and the ability of the system to anticipate curves. Results found are very promising.

关键词： computational intelligence Fuzzy neural networks Fuzzy control Competitive intelligence Road safety Road accidents Hybrid intelligent systems Intelligent networks Road transportation Remotely operated vehicles

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control solutions for vehicles with continuously variable transmission

Control solutions for vehicles with continuously variable tr...

引用

International symposium on computational intelligence and Informatics

作者： C.-A. Dragos S. Preitl R.-E. Precup C.-S. Nes D. Pirlea A. S. Paul Department of Automation and Applied Informatics Polytechnic University of Timisoara Timisoara Romania Department of Strength of Materials Polytechnic University of Timisoara Timisoara Romania

The paper presents aspects concerning the modeling, driving scenarios and control structures of two classes of vehicular power train systems with continuously variable transmission (CVT). The modeling includes an analysis of the systems' components which include the spark-ignition internal combustion engine, the torque converter, the continuously variable transmission and the wheels. The CVT offers a continuum of infinitely variable gear ratios between established minimum and maximum limits compared to the automatic transmission which has only five gear ratios. Five driving scenarios are illustrated by digital simulation results: acceleration, overtaking maneuver, ramp encounter, engine brake, and cruise. Digital simulations are presented to test and validate the developed control solutions for one driving scenario.

关键词： Vehicles Engines Torque Mathematical model Gears Acceleration Mechanical power transmission

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Utility Ethernet network architecture: Networked Electrical eXchange Topology-NEXT

Utility Ethernet network architecture: Networked Electrical ...

引用

ieee Princeton Section Sarnoff symposium

作者： Tom R. Janca Utility Ethernet Forum USA

Critical infrastructure networks serving electrical power systems across geographical transmission and distribution tiers using Ethernet or IP based protocols require electrical utility network architectural concepts and approaches suited to electrical circuit protection, control, instrumentation and automation. A private Utility Ethernet Layer 2 switched network mixed with WDM serving medium and wide area geographic regions whose domains are aligned with electrical transmission and distribution circuit system services is recommended. Architecture philosophy is described as Networked Electrical eXchanges Typology (NEXT) an original concept to direct and define network service domains and actors in alignment with electrical circuit elements to create static logical links reliant on switching at the access and aggregation levels. NEXT concepts reduce penetration of Layer 3 or Label routing at the networks access edge reducing circuit element network threat exposure improving NERC CIP compliance. Layer 2 MAN and WAN NEXT architectural approaches further improve network synchronized performance and enable WAN distribution of common network timing through ieee 1588 and SyncE Ethernet Precision Time Protocols (PTP). NEXT architectural concepts are intended to advance and prepare for grid automation and evolve into future distributed intelligence systems compared with today's centralized control and operations.

关键词： Substations automation Instruments Synchronization Computer architecture Wide area networks Artificial intelligence

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computational intelligence in control-a comparison of several neuro-fuzzy systems

Computational intelligence in control-a comparison of severa...

引用

ieee International symposium on Industrial Electronics (ISIE)

作者： M.B. Gorzalczany A. Gluszek Department of Electrical and Computer Engineering Kielce University of Technology Kielce Poland

ISBN: (纸本)0780366069

The aim of this paper is to present and compare several neuro-fuzzy systems used as controllers for simulated backing up of a truck to a loading dock in a planar parking lot. The following systems have been considered: nfCon-the system proposed in this paper, an alternative neuro-fuzzy system reported in literature as well as the well-known ANFIS and NFIDENT systems. The main criterion of comparison of all systems is their performance (the accuracy of functioning) versus interpretability the transparency and the ability to explain generated actions; it also includes an analysis and pruning of the obtained fuzzy-rule bases.

关键词： computational intelligence control systems Fuzzy neural networks Fuzzy logic Artificial neural networks Performance analysis control system synthesis Fuzzy systems computational modeling Computer simulation

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Nonlinear model predictive control using a recurrent neural network

Nonlinear model predictive control using a recurrent neural ...

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International Joint Conference on Neural Networks (IJCNN)

作者： Yunpeng Pan Jun Wang Department of Mechanical and Automation Engineering Chinese University of Hong Kong New Territories Hong Kong China

As linear model predictive control (MPC) becomes a standard technology, nonlinear MPC (NMPC) approach is debuting both in academia and industry. In this paper, the NMPC problem is formulated as a convex quadratic programming problem based on nonlinear model prediction and linearization. A recurrent neural network for NMPC is then applied for solving the quadratic programming problem. The proposed network is globally convergent to the optimal solution of the NMPC problem. Simulation results are presented to show the effectiveness and performance of the neural network approach.

关键词： Artificial neural networks Quadratic programming Biological neural networks Optimization Process control Predictive models Recurrent neural networks

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ieee Workshop on computational intelligence in Biometrics and Identity Management (CIBIM)

作者： Hengyi Zhang Chaoying Tang Xiaojie Li Adams Wai Kin Kong School of Computer Engineering Nanyang Technological University Singapore College of Automation Nanjing University of Aeronautics and Astronautics Nanjing P.R. China Nanyang Technological University Singapore Singapore SG

Vein patterns have been used in commercial biometric systems for many years and are recently considered for criminal authentication. Understanding the similarity between genetically identical vein patterns is important, especially when using them in legal cases involving identical twins. Vein patterns sharing the same Deoxyribonucleic acid (DNA) sequence are generally regarded as vein patterns with maximum similarity. If they are completely distinguishable, it implies that the uniqueness of vein patterns is high. Though the genetic dependence of other biometric traits, including fingerprints, faces, palmprints, and irises, have been studied, genetically identical vein patterns have not been studied systematically. With the help of an automatic vein pattern matching algorithm, this paper analyzes and measures the similarity between genetically identical vein patterns. 234 genetically identical forearm pairs and 204 genetically identical thigh pairs were collected for this study. Experimental results indicate that genetically identical vein patterns have extra similarity, but they are distinguishable.

关键词： Veins Skin Thigh Thumb Pattern matching Fingerprint recognition

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Emotion Recognition Using Time-frequency Analysis of EEG Signals and Machine Learning*

Emotion Recognition Using Time-frequency Analysis of EEG Sig...

引用

ieee symposium Series on computational intelligence (SSCI)

作者： Jianhua Zhang Peng Chen Stefano Nichele Anis Yazidi Department of Computer Science Oslo Metropolitan University Oslo Norway Department of Automation East China U. of Sci. & Tech. Shanghai P.R. China

ISBN: (数字)9781728124858

ISBN: (纸本)9781728124865

In recent years, emotion recognition has drawn intense interest from researchers in various fields. Because of their intrinsic correlation with emotions, physiological signals based emotion recognition method is objective and insusceptible to intentional disguise of the subject under study. In particular, electroencephalogram (EEG) signals are known to be responsive and sensitive to variations in emotional state. In this paper, a 4- class emotion classification problem is investigated. Firstly, a clustering algorithm is used to determine the target class of each emotion-related data. Then wavelet analysis is used to extract features from 32-channel EEG signals. Finally, we compare five feature dimensionality reduction or feature selection algorithms and four types of machine learning based classifiers. The comprehensive comparative results show the effectiveness of the combination of EEG feature dimensionality reduction algorithm and random forest (RF) for multi-class emotion recognition problem under study.

关键词： Handheld computers Electroencephalography Feature extraction Machine learning computational intelligence Affective computing Wavelet transforms

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A Bayesian model for RTS units control applied to StarCraft

A Bayesian model for RTS units control applied to StarCraft

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ieee symposium on computational intelligence and Games, CIG

作者： Gabriel Synnaeve Pierre Bessière School of Science Wuhan Institute of Technology Wuhan China School of Management Wuhan Institute of Technology Wuhan China

In real-time strategy games (RTS), the player must reason about high-level strategy and planning while having effective tactics and even individual units micro-management. Enabling an artificial agent to deal with such a task entails breaking down the complexity of this environment. For that, we propose to control units locally in the Bayesian sensory motor robot fashion, with higher level orders integrated as perceptions. As complete inference encompassing global strategy down to individual unit needs is intractable, we embrace incompleteness through a hierarchical model able to deal with uncertainty. We developed and applied our approach on a StarCraft 1 AI.

关键词： Bayesian methods Games Planning Robot sensing systems Artificial intelligence Cognition Uncertainty

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