Filters








36 Hits in 8.0 sec

A Review of Artificial Intelligence Algorithms Used for Smart Machine Tools

Chih-Wen Chang, Hau-Wei Lee, Chein-Hung Liu
2018 Inventions  
Many studies have been made on the diagnosis and detection of mechanical components over the last few decades: a neural network (NN) algorithm for motor rolling bearing fault diagnosis [68], the artificial  ...  of deep learning (DL) methods [12], the RNN scheme for machine health monitoring [13], machine health monitoring using convolutional bi-directional LSTM networks [14], the convolutional neural networks  ...  classification phases of motor fault detection into a single learning body.  ... 
doi:10.3390/inventions3030041 fatcat:6qrwhmrl2bfwrgmovqvsyx5p3y

Engineering Applications of Intelligent Monitoring and Control 2014

Qingsong Xu, Pak-Kin Wong, Minping Jia, Chengjin Zhang, Ping-Lang Yen
2015 Mathematical Problems in Engineering  
Following the inaugural special issue, the main focus of this year's annual issue is on emerging intelligent system approaches with the goal of monitoring and controlling various physical processes with  ...  's "Rotor Resistance Online Identification of Vector Controlled Induction Motor Based on Neural Network" proposes a novel model for rotor resistance parameters identification based on Elman neural networks  ...  To solve this problem, a fault diagnosis method combining Hilbert-Huang transform (HHT), singular value decomposition (SVD), and Elman neural network is proposed in H. Liu et al.  ... 
doi:10.1155/2015/523156 fatcat:h7ck7y34lbg7tbc3gluhvesyd4

Artificial Neural Networks Based Optimization Techniques: A Review

Maher G. M. Abdolrasol, S. M. Suhail Hussain, Taha Selim Ustun, Mahidur R. Sarker, Mahammad A. Hannan, Ramizi Mohamed, Jamal Abd Ali, Saad Mekhilef, Abdalrhman Milad
2021 Electronics  
In this paper, we present an extensive review of artificial neural networks (ANNs) based optimization algorithm techniques with some of the famous optimization techniques, e.g., genetic algorithm (GA),  ...  This paper emphasizes enhancing the neural network via optimization algorithms by manipulating its tuned parameters or training parameters to obtain the best structure network pattern to dissolve the problems  ...  An Elman neural network was used to train the connection weights between the layers based on a whale optimization algorithm (WOA) to solve the problem of falling into local best solutions [189] .  ... 
doi:10.3390/electronics10212689 fatcat:oupnikhxdbhedfz5yeatmtj4xa

Program

2009 2009 International Joint Conference on Neural Networks  
P1421 Synthesis of Crossed Dipole Frequency Selective Surfaces Using Genetic Algorithms and Artificial Neural Networks Rossana Cruz, Paulo Silva and Adaildo D'Assuncao P1422 Learning on Class Imbalanced  ...  based Neural Controller as Optimized by Particle Swarm Algorithm using Dual 11:50AM A Study of the Effect of Noise Injection on the Training of Artificial Neural Networks Yulei Jiang, Richard Zur, Lorenzo  ... 
doi:10.1109/ijcnn.2009.5178575 fatcat:kxaceopferd23ps5uyrn3m7xjy

Computational Intelligence in the Context of Industry 4.0 [chapter]

Alexander Hošovský, Ján Piteľ, Monika Trojanová, Kamil Židek
2021 Implementing Industry 4.0 in SMEs  
The ending part of the chapter is focused on connecting theory and practice in a case study, which lists industrial parts recognition by convolutional neural networks for assisted assembly.  ...  Each subchapter provides fundamentals of some paradigms, followed by the use of CI in the concrete paradigm.  ...  Long short-term memory (LSTM) networks are a special type of recurrent neural networks (Fig. 2.10) , which uses a different architecture compared to standard RNNs like Elman or Jordan.  ... 
doi:10.1007/978-3-030-70516-9_2 fatcat:3bgkvenwcvcqvnlfmhmjeoyury

Intelligent Approaches in Locomotion - A Review

Joe Wright, Ivan Jordanov
2014 Journal of Intelligent and Robotic Systems  
Among the investigated intelligent approaches for solving locomotion problems are oscillator based Central Pattern Generators, Neural Networks, Hidden Markov models, Rule Based and Fuzzy Logic systems,  ...  The parameterisation techniques cover a range of approaches, from simple manual specification to evolutionary algorithms.  ...  Table 4 : 4 Number of simulations used in evolving solutions using genetic algorithms, in a sample of publications covering rule based, CPG and neural network control methods.  ... 
doi:10.1007/s10846-014-0149-z fatcat:wpzs5i4lsbhxfdgkf5i7ij6xa4

Prognostics and Health Management in Nuclear Power Plants: An Updated Method-Centric Review With Special Focus on Data-Driven Methods

Xingang Zhao, Junyung Kim, Kyle Warns, Xinyan Wang, Pradeep Ramuhalli, Sacit Cetiner, Hyun Gook Kang, Michael Golay
2021 Frontiers in Energy Research  
much greater and more diverse than with the current plants.  ...  The NPP equipment PHM is one area where the application of these algorithmic advances can significantly improve the ability to perform asset management.  ...  al. (2018) tested the effectiveness of an RBF network and an Elman neural network (ENN) after using PCA to perform noise filtering for NPP fault diagnosis.Another common trend, both in the literature  ... 
doi:10.3389/fenrg.2021.696785 fatcat:4x4pgevfsrbhrihmdsrdegyptu

Artificial Intellgence – Application in Life Sciences and Beyond. The Upper Rhine Artificial Intelligence Symposium UR-AI 2021 [article]

Karl-Herbert Schäfer
2021 arXiv   pre-print
The TriRhenaTech alliance is a network of universities in the Upper-Rhine Trinational Metropolitan Region comprising of the German universities of applied sciences in Furtwangen, Kaiserslautern, Karlsruhe  ...  , Offenburg and Trier, the Baden-Wuerttemberg Cooperative State University Loerrach, the French university network Alsace Tech (comprised of 14 'grandes \'ecoles' in the fields of engineering, architecture  ...  Neural Networks for Data Augmentation The neural networks can now be trained with the prepared training data as described above.  ... 
arXiv:2112.05657v1 fatcat:wdjgymicyrfybg5zth2dc2i3ni

Sliding bifurcations in resonant inverters

Enrique Ponce, Luis Benadero, Abdelali El Aroudi, Luis Martinez-Salamero
2017 2017 14th International Multi-Conference on Systems, Signals & Devices (SSD)  
Results were taken to train two multi-layers perceptron neural networks.  ...  The second phase uses the result of the first phase to train a neural network that preform on-line diagnosis and puts into practice the developed theoretical approach.  ... 
doi:10.1109/ssd.2017.8167001 dblp:conf/IEEEssd/PonceBAM17 fatcat:6lbol63imjffhezjv6yc6cnheu

Thorough state-of-the-art analysis of electric and hybrid vehicle powertrains: Topologies and integrated energy management strategies

Dai-Duong Tran, Majid Vafaeipour, Mohamed El Baghdadi, Ricardo Barrero, Joeri Van Mierlo, Omar Hegazy
2019 Renewable & Sustainable Energy Reviews  
Network Learning Elman Neural Network - [205] - - - - - Artificial Neural Network [206] - [207] --- [208] emission species over the driving cycle.  ...  Factor EGR Exhaust Gas Recirculation EM Electric Motor EMS Energy Management Strategy ENN Elman Neural Network ES Extremum Seeking ESS Energy Storage System EVT Electric Variable Transmission  ... 
doi:10.1016/j.rser.2019.109596 fatcat:ybks774km5htvb6f7foyetum7m

Being There: Putting Brain, Body and World Together Again

Tim van Gelder, Andy Clark
1998 Philosophical Review  
Randall Beer and John Gallagher (1992) have used genetic algorithms to evolve neural network controllers for insect locomotion.  ...  Thus experience with drawing and using Venn diagrams allows us to train a neural network which subsequently allows us to manipulate imagined Venn diagrams in our heads.  ...  Each icon represents a particular visual stimulus, and its color represents the mean response to that stimulus relative to the spontaneous background rate, using the color scale shown above.  ... 
doi:10.2307/2998391 fatcat:6odpcm5iurgi3kickjadxvghzu

Language impairment and colour categories

Jules Davidoff, Claudio Luzzatti
2005 Behavioral and Brain Sciences  
Although we take no stance on which position is to be accepted as final truth with respect to human categorisation and naming, we do point to theoretical constraints that make each position more or less  ...  Minett and Wong Chun-Kit for their useful discussions and resourceful suggestions.  ...  This said, we find several faults with it, including their inconsistent use of arguments, and their poor usage of evolutionary algorithms.  ... 
doi:10.1017/s0140525x05280081 fatcat:ejj2h2zl5jcp5njzbtgtjurzq4

Coordinating perceptually grounded categories through language: A case study for colour

Luc Steels, Tony Belpaeme
2005 Behavioral and Brain Sciences  
Minett and Wong Chun-Kit for their useful discussions and resourceful suggestions.  ...  This said, we find several faults with it, including their inconsistent use of arguments, and their poor usage of evolutionary algorithms.  ...  neural networks.  ... 
doi:10.1017/s0140525x05000087 pmid:16209771 fatcat:ea62tuwiq5gyxkigbkjf3paidu

Natural ethical facts: evolution, connectionism, and moral cognition

2004 ChoiceReviews  
Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently  ...  same way that the contents of the training set are all important for an artificial neural network, so is the training set content that we use to configure our moral biological connectionist network.  ...  Two networks are trained.  ... 
doi:10.5860/choice.41-4572 fatcat:aphgx4ubazh5zaanxfe3tfuzda

Table of contents

2019 2019 Chinese Control Conference (CCC)   unpublished
ZHAO Dong, JIANG Bin, YANG Hao, TAO Gang 4931 Convolutional Neural Network for Fault Diagnosis of High-Speed Train Bogie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ...  SHI Xiaodi, YAN Liping, XIA Yuanqing 3450 On the Potential of Geomagnetism-aided Vehicle In-out Detection Using BLE RSS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ... 
doi:10.23919/chicc.2019.8866607 fatcat:bkwxxogrqvcmfpmqiek3xgnuoe
« Previous Showing results 1 — 15 out of 36 results