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Robust Control, Optimization, and Applications to Markovian Jumping Systems
2014
Abstract and Applied Analysis
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systems, networked control systems, time-delayed systems, neural networks, the Takagi-Sugeno fuzzy systems, simulated annealing, and fault detection methods. ...
in this special issue include stochastic stability, stabilization, stochastic control optimization, system modeling and identification methods, predictive control, signal processing, robust filtering, multiagent ...
The paper entitled "Boundary recognition by simulating a diffusion process in wireless sensor networks" by D. ...
doi:10.1155/2014/582549
fatcat:wamtzydcezhwfnwbo5vgcmhq5y
Stochastic Systems: Modeling, Optimization, and Applications
2014
Mathematical Problems in Engineering
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systems, nonlinear systems, time-delayed systems, neural networks, T-S fuzzy systems, simulated annealing, and fault diagnosis methods. ...
Many stochastic systems, such as switching systems, Markovian jumping systems, jumping neural networks, T-S fuzzy jumping systems and network control systems, have arisen naturally in the mathematical ...
Lu et al. proposes a new despeckling algorithm based on directionlets using multiscale products. ...
doi:10.1155/2014/713969
fatcat:5r3xcqxccjeoln5c6tafplu63m
Recurrent Deep Multiagent Q-Learning for Autonomous Brokers in Smart Grid
2018
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence
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We use real household electricity consumption data to simulate the retail market for evaluating our strategy. ...
In this paper, we develop an effective pricing strategy for brokers in local electricity retail market based on recurrent deep multiagent reinforcement learning and sequential clustering. ...
The neural network structure is already shown in Figure 2 . ...
doi:10.24963/ijcai.2018/79
dblp:conf/ijcai/YangHSWFS18
fatcat:uel4adcwpbcclevqtm73u6d6ae
mt5se: An Open Source Framework for Building Autonomous Trading Robots
[article]
2022
arXiv
pre-print
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These initiatives include traditional neural networks, fuzzy logic, reinforcement learning but also more recent approaches like deep neural networks and deep reinforcement learning. ...
Furthermore, we discuss the simple architecture that is used in many studies and propose an alternative multiagent architecture. ...
] , neural networks [40] , Bayesian dynamic networks [41] , reinforcement learning [42] and so on. ...
arXiv:2101.08169v3
fatcat:z56qcy7gmncd3guv4pybsg57n4
Introduction to the special issue on neural networks in financial engineering
2001
IEEE Transactions on Neural Networks
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They use their multiagent representation to model and hence forecast multiple foreign exchange markets. ...
They use recurrent neural networks, and compare it with a fixed-order Markov model and GARCH. ...
His interests include econometrics, statistics, artificial neural networks, forecasting, and financial markets. Dr. ...
doi:10.1109/tnn.2001.935079
fatcat:r4mg7cefljb2vi2spmc7qlk32m
2020 Index IEEE Transactions on Systems, Man, and Cybernetics: Systems Vol. 50
2020
IEEE Transactions on Systems, Man & Cybernetics. Systems
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Networks With Partial Mea-Distributed Fault Estimation for a Class of Nonlinear Multiagent Systems. theses: Theory and Simulation. ...
., +, TSMC Sept. 2020 3401-3411 Adaptive Discrete Event Simulation Systems to Embrace Changes of Observer-Based Consensus of Nonlinear Multiagent Systems With Relative A Neural Adaptive Approach for Active ...
doi:10.1109/tsmc.2021.3054492
fatcat:zartzom6xvdpbbnkcw7xnsbeqy
A REVIEW ON FRAMEWORKS FOR DECISION SUPPORT SYSTEMS FOR ENVIRONMENTAL DOMAINS
1970
Eidos
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review is devoted to related research and presents an overview of current research in areas of complex system analysis and decision making by the means of intelligent tools, including those that are agent-based ...
Software agents. [33] The results obtained from two different neural networks are compared. To predict traffic related PM 2.5 and PM 10 emissions by an artificial neural networks based model. ...
Feed Forward and Radial Basis Function neural networks. ...
doi:10.29019/eidos.v0i4.84
fatcat:5zx4cyw7i5gvvpmo22ryovqlwa
Agents in industry: the best from the AAMAS 2005 industry track
2006
IEEE Intelligent Systems
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The articles in this department intend to give some indication of agent technology's readiness for commercial deployment, based primarily on the presentations and discussions at the inaugural Industry ...
Reduction of unpredictability in the trade portfolio reduces imbalance costs charged to the trader by the independent network operator. ...
People often view agent technology as a black-box technology (like neural networks or genetic algorithms) that you can insert to solve a particular complex problem. ...
doi:10.1109/mis.2006.19
fatcat:66r27spkmnacppwhzpu6rmco6e
AI in Finance: Challenges, Techniques and Opportunities
[article]
2021
arXiv
pre-print
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Typical methods include various classic artificial neural networks (ANN), recurrent neural networks (RNN), wavelet neural networks, genetic neural networks, fuzzy neural networks, and DNN variants including ...
GNN), deep Bayesian networks and neural language models (e.g., Transformer) can be used for the above EcoFin purposes. ...
arXiv:2107.09051v1
fatcat:g62cz4dqt5dcrbckn4lbveat3u
Design and Implementation of Novel Artificial Neural Network Based Stock Market Forecasting System on Field-Programmable Gate Arrays
2011
American Journal of Applied Sciences
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Problem statement: Multiagent system is very proficient and has rules well-suited for financial forecast with its neural network. ...
of the neural network mechanism. ...
CONCLUSION By simulating with KLSE index data the proposed stock market forecasting system based on neural network is successfully designed, implemented and tested on FLEX 10KE FPGA chip. ...
doi:10.3844/ajassp.2011.1054.1060
fatcat:pfhiyzyinjfffo2oxmmjvrp2fi
Data science and AI in FinTech: An overview
[article]
2021
arXiv
pre-print
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sciences, and agent-based modeling and simulation, etc. ...
Neural computing methods Wavelet neural network, genetic neural network, recurrent neural network, deep neural networkMacroeconomic and microeconomic factor correlation analysis, valuation and pricing ...
arXiv:2007.12681v2
fatcat:jntzuwaktjg2hmmjypi5lvyht4
A Multiagent Approach to $Q$-Learning for Daily Stock Trading
2007
IEEE transactions on systems, man and cybernetics. Part A. Systems and humans
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Index Terms-Financial prediction, intelligent multiagent systems, portfolio management, Q-learning, stock trading. ...
Motivated by this, we present a new stock trading framework that attempts to further enhance the performance of reinforcement learning-based systems. ...
The same neural network structure was used for all the agents of MQ-Trader. ...
doi:10.1109/tsmca.2007.904825
fatcat:zhd7ymsfxnhprjqptezxgopyai
Data science and AI in FinTech: an overview
2021
International Journal of Data Science and Analytics
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sciences, and agent-based modeling and simulation, etc. ...
These tasks apply deep learning models, including basic deep neural networks and their recent developments, such as diversified deep neural mechanisms, architectures and networks (e.g., recurrent neural ...
doi:10.1007/s41060-021-00278-w
fatcat:4qo3swacjbaaxh56p5bvhmjzqa
2021 Index IEEE Transactions on Neural Networks and Learning Systems Vol. 32
2021
IEEE Transactions on Neural Networks and Learning Systems
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., +, TNNLS Feb. 2021 748-762 Reachable Set Estimation for Neural Network Control Systems: A Simulation-Guided Approach. ...
., +, TNNLS June 2021 2610-2621 Reachable Set Estimation for Neural Network Control Systems: A Simulation-Guided Approach. ...
Image coding Deep Multiscale Detail Networks for Multiband Spectral Image Sharpening. ...
doi:10.1109/tnnls.2021.3134132
fatcat:2e7comcq2fhrziselptjubwjme
New Developments in Mathematical Control and Information for Fuzzy Systems
2013
Mathematical Problems in Engineering
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In this paper entitled "Fuzzy PD control of networked control systems based on CMAC neural network" by L. Huang and J. ...
Wang, a classifying fuzzy-neural approach, based on the combination of principal component analysis (PCA), fuzzy cmeans (FCM), and back propagation network (BPN), is proposed to estimate the cycle time ...
Acknowledgments The guest editors would like to thank all the authors of this special issue for contributing the high quality papers, and we hope the reader will share our joy and find this special issue very useful ...
doi:10.1155/2013/126878
fatcat:jqd2cnhbrvexnb3uceubjego54
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