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Explainable AI: current status and future directions
[article]
2021
arXiv
pre-print
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to unbox complex neural networks. ...
It propogates predictions backward in the neural network. ...
arXiv:2107.07045v1
fatcat:f3nishdh45chjcdeu4yiie5eoq
Automobile Maintenance Prediction Using Deep Learning with GIS Data
2019
Procedia CIRP
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An experimental study based on real-world maintenance data reveals that the performance of deep neural network improved with the help of GIS data. ...
An experimental study based on real-world maintenance data reveals that the performance of deep neural network improved with the help of GIS data. ...
Because deep belief network does not rely on explicit model equations and domain knowledge, Zhao et al. [7] introduced a deep belief network to predict the RUL of bearing. ...
doi:10.1016/j.procir.2019.03.077
fatcat:gxyou5gfzfco5ops3isl3ygdce
Fault diagnosis and health management of bearings in rotating equipment based on vibration analysis – a review
2021
Journal of Vibroengineering
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There is an ever-increasing need to optimise bearing lifetime and maintenance cost through detecting faults at earlier stages. ...
This can be achieved through improving diagnosis and prognosis of bearing faults to better determine bearing remaining useful life (RUL). ...
One of the methods used by Deutsch [61] was the Deep Belief Network. ...
doi:10.21595/jve.2021.22100
fatcat:erdumydfzvg7bagqjfggy256my
The application of reasoning to aerospace Integrated Vehicle Health Management (IVHM): Challenges and opportunities
2019
Progress in Aerospace Sciences
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A fully functional IVHM system is required to optimize Condition Based Maintenance (CBM), avoid unplanned maintenance activities and reduce the costs inflicted thereupon. ...
HEAL-THYLIFE, used in smartphones for recognizing user behaviors, applies Answer set programming based Stream Reasoning along with Artificial Neural Networks [37] . ...
The reasoner maintenance system can be either assumption based or justification based [45] . The Tasks module of the reasoning system contains its objective or goal for a given problem. ...
doi:10.1016/j.paerosci.2019.01.001
fatcat:puttw3jolndz5awzq5utyegp3m
An ambient agent architecture exploiting automated cognitive analysis
2011
Journal of Ambient Intelligence and Humanized Computing
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In this paper an agent-based ambient agent architecture is presented based on monitoring human's interaction with his or her environment and performing cognitive analysis of the causes of observed or predicted ...
In such a way the ambient agent model is able to provide a more in depth cognitive analysis of causes of (un)satisfactory performance and based on this analysis to generate interventions in a knowledgeable ...
Thus, neural network-based methods may derive information about this state only indirectly. ...
doi:10.1007/s12652-011-0048-0
fatcat:ihpsopqms5h6jdncscdzlkk7au
The Evolution of Computational Agency
[chapter]
2020
Handbook of Research on Computational Science and Engineering
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2021 pre-print arXiv:2112.05575v1 fatcat:54cnrhtrb5evbm6dwb67ugbbtm
Advances in hardware like GPUs that brought neural networks back to life may also similarly infuse new life into agent-based models and pave the way for significant advancements in research on artificial ...
Agent-based models have emerged as a promising paradigm for addressing ever increasing complexity of information systems. ...
A related application area that have used the rational choice paradigm for modeling agents, is multi-agent networks. ...
doi:10.4018/978-1-7998-2975-1.ch001
fatcat:dcfiemv2gza7rbizr56ug6cqua
Cognitive Neuropsychiatric Models of Persecutory Delusions
2001
American Journal of Psychiatry
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Method: The authors present a comprehensive review of the literature, citing results of relevant functional neuroimaging and neural network studies. ...
Objective: The major cognitive theories of persecutory delusion formation and maintenance are critically examined in this article. ...
Neural network models of persecutory delusions highlight the importance of disordered neuromodulation in their formation and of disordered neuroplasticity in their maintenance. ...
doi:10.1176/appi.ajp.158.4.527
pmid:11282685
fatcat:jhuzzkojtbb5dkawoguxowq4bi
A Comparison of Text Retrieval Models
1992
Computer journal
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In this paper we introduce a recent form of the probabilistic model based on inference networks, and show how the vector space and exact-match models can be described in this framework. ...
The retrieval effectiveness of strategies based on these models has been evaluated experimentally, but there has been little in the way of comparison in terms of their formal properties. ...
The same justification cannot be made for many commercial IR systems that also ignore retrieval models based on uncertainty. ...
doi:10.1093/comjnl/35.3.279
fatcat:bwipc6ljsvbkbdwxlemj5f43vi
Data Analysis for the Aero Derivative Engines Bleed System Failure Identification and Prediction
2021
International Journal of Intelligent Systems and Applications
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If the engine operates with BOV system impaired, this leads to the high maintenance cost during overhaul, increased emission rate, fuel consumption and loss in the efficiency. ...
Middle size gas/diesel aero-derivative power generation engines are widely used on various industrial plants in the oil and gas industry. ...
The paper describes the utilized deep learning architectures such as, Long Short-Term Memory (LSTM), Deep Belief Network (DBN), Deep Autoencoders (DAE) and Convolutional Neural Networks (CNN) and suggests ...
doi:10.5815/ijisa.2021.06.02
fatcat:4ldn4ltbbnfplfqwusqv2burs4
Decision support systems for clinical radiological practice — towards the next generation
2010
British Journal of Radiology
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More importantly, we discuss the specific design, performance and usage characteristics that previous systems have highlighted as being necessary for clinical uptake and routine use. ...
Within radiology, the recent development of quantitative imaging techniques, such as perfusion imaging, and the development of imaging-based biomarkers in modern therapeutic assessment has highlighted ...
We then review more recent systems based around neural networks designed to emulate human reasoning techniques. ...
doi:10.1259/bjr/33620087
pmid:20965900
pmcid:PMC3473729
fatcat:ovbi2rb6tzccppkwkiinc7lywq
Applications of Artificial Intelligence in Fire Safety of Agricultural Structures
2021
Applied Sciences
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Even though artificial neural networks (ANNs), genetic algorithms (GAs), probabilistic neural networks (PNNs), and adaptive neurofuzzy inference systems (ANFISs), among others, have proven useful in fire ...
Most farms rely on traditional/non-technology-based methods of fire prevention. ...
inference systems (ANFISs), artificial neural networks (ANNs) [34] , probabilistic neural networks (PNNs), recurrent LSTM neural networks (R-LSTM-NNs), and deep belief networks (DBNs). ...
doi:10.3390/app11167716
fatcat:7nztla6zcvhlxoyvn4k36d4pgm
Software Assurance in an Uncertain World
[chapter]
2019
Lecture Notes in Computer Science
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From financial services platforms to social networks to vehicle control, software has come to mediate many activities of daily life. ...
That is, experts try to build (safety-critical) systems carefully according to well justified methods and articulate these justifications in an assurance case that is ultimately judged by a human. ...
The approaches which use BBNs treat safety goals as nodes in the network and try to compute their conditional probability based on given probabilities for the leaf nodes of the network. ...
doi:10.1007/978-3-030-16722-6_1
fatcat:4nsmyp5govgerjxnme4site34y
The Cognitive–Affective Structure of Political Ideologies
[chapter]
2015
Emotion in Group Decision and Negotiation
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Each of these is a system of interconnected concepts, beliefs, goals, and attitudes. ...
This chapter attempts to answer these questions using novel accounts of the structure and development of conceptual systems. ...
This process can be precisely described using equations for information processing in neural networks, but mathematical details are omitted here. ...
doi:10.1007/978-94-017-9963-8_3
fatcat:lrx3myhopvfxhmd6uyauoza6ii
Epistemic value in the subpersonal vale
2020
Synthese
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primary-role in much epistemically relevant cognition and thus constitute a domain in which we might reasonably expect to locate the "missing source" of epistemic value, beyond the value attached to mere true belief ...
Approaching the issue of integration from a slightly different angle, consider the problem of catastrophic interference, which afflicts many neural network models of learning and remembering; this problem ...
To the extent that one has justification for one's existing beliefs, consistency or coherence with them provides justification for a newly formed belief (or belief-like state). ...
doi:10.1007/s11229-020-02631-1
fatcat:riosztxmfnbizddgztnfxb7tdm
An Integrated Approach of Belief Rule Base and Deep Learning to Predict Air Pollution
2020
Sensors
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Belief Rule Based Expert System (BRBES), a knowledge-driven approach, is a widely employed prediction algorithm to deal with such uncertainties based on knowledge base and inference engine. ...
use cases of sensor data stream where prediction is vital to protect people and assets. ...
Acknowledgments: This research is based on the Master's Thesis [60] of Sami Kabir, conducted at the Pervasive and Mobile Computing Laboratory, Luleå University of Technology, Skellefteå, Sweden. ...
doi:10.3390/s20071956
pmid:32244380
pmcid:PMC7181062
fatcat:efkzbpmr6rgapeqm62qz7otksy
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