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 |  موضوع: كتاب Intelligent Information Processing with Matlab الخميس 04 يوليو 2024, 3:35 pm | |
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أخواني في الله
أحضرت لكم كتاب
Intelligent Information Processing with Matlab
Xiu Zhang, Xin Zhang and Wei Wang
و المحتوى كما يلي :
Contents
1 Artiϐicial Neural Network
1. 1 Artiϐicial Neuron
1. 2 Overview of Artiϐicial Neural Network
1. 3 Backpropagation Neural Network
1. 4 Hopϐield Neural Network
1. 5 Competitive Neural Network
1. 6 Deep Neural Network
References
2 Convolutional Neural Network
2. 1 Overview of Convolutional Neural Network
2. 2 Neural Network Performance Evaluation
2. 3 Transfer Learning with Convolutional Neural Network
2. 4 Research Progress of Neural Network
References
3 Fuzzy Computing
3. 1 Overview of Fuzzy Computing
3. 2 Fuzzy Sets
3. 3 Fuzzy Pattern Recognition
3. 4 Fuzzy Clustering
3. 5 Fuzzy Inference
3. 6 Fuzzy Control System
3. 7 Fuzzy Logic Designer
References
4 Fuzzy Neural Network
4. 1 Overview of Fuzzy Neural Network4. 2 Adaptive Fuzzy Neural Inference System
4. 3 Time Series Prediction
4. 4 Interval Type-2 Fuzzy Logic
4. 5 Fuzzy C-means Clustering
4. 6 Suburban Commuting Prediction Problem
4. 7 Research Progress of Fuzzy Computing
References
5 Evolutionary Computing
5. 1 Overview of Evolutionary Computing
5. 2 Simple Genetic Algorithm
5. 3 Genetic Algorithm for Travelling Salesman Problem
5. 4 Ant Colony Optimization Algorithm
5. 5 Particle Swarm Optimization Algorithm
5. 6 Differential Evolution Algorithm
References
6 Testing and Evaluation of Evolutionary Computing
6. 1 Test Set of Traveling Salesman Problem
6. 2 Test Set of Continuous Optimization Problem
6. 3 Evaluation of Continuous Optimization Problems
6. 4 Artiϐicial Bee Colony Algorithm
6. 5 Fireworks Algorithm
6. 6 Research Progress of Evolutionary Computing
References
References
1. Yue CT, Price KV, Suganthan PN, Liang JJ, Ali MZ, Qu BY, Award NH, Biswas PP (2020) Problem
Deϐinitions and evaluation Criteria for the CEC 2020 special session and competition on single
objective bound constrained numerical optimization. Technical Report 201911,Computational Intelligence Laboratory, Zhengzhou University, Zhengzhou China, Nanyang
Technological University, Singapore
2. Tan Y (2015) Fireworks algorithm: a novel swarm intelligence optimization method. Springer,
Berlin
[Crossref][zbMATH]
3. Li J, Tan Y (2020) A comprehensive review of the ϐireworks algorithm. ACM Comput Survey
52:1–28
[Crossref]
4. Shi Y (2011) Brain storm optimization algorithm. In: Tan Y, Shi Y, Chai Y, Wang G (eds)
Advances in swarm intelligence. ICSI 2011. Lecture notes in computer science, vol 6728.
Springer, Berlin, Heidelberg, pp 303–309
5. Duan H, Qiao P (2014) Pigeon-inspired optimization: a new swarm intelligence optimizer for
air robot path planning. Int J Intell Comput Cybern 7:24–37
[MathSciNet][Crossref]
6. Cheng S, Qin Q, Chen J et al (2016) Brain storm optimization algorithm: a review. Artif Intell
Rev 46:445–458
[Crossref]
7. Duan H, Huo M, Shi Y (2020) Limit-cycle-based mutant multiobjective pigeon-inspired
optimization. IEEE Trans Evol Comput 24(5):948–959
[Crossref]
8. Mehanović D, Kečo D, Kevrić J et al (2021) Feature selection using cloud-based parallel genetic
algorithm for intrusion detection data classiϐication. Neural Comput Applic 33:11861–11873.
https://doi.org/10.1007/s00521-021-05871-5
[Crossref]
9. Liang Z, Qin Q, Zhou C (2022) An image encryption algorithm based on Fibonacci Q-matrix
and genetic algorithm. Neural Comput Applic 34:19313–19341. https://doi.org/10.1007/
s00521-022-07493-x
[Crossref]
10. Nguyen TPQ, Kuo RJ, Le MD et al (2022) Local search genetic algorithm-based possibilistic
weighted fuzzy c-means for clustering mixed numerical and categorical data. Neural Comput
Applic 34:18059–18074. https://doi.org/10.1007/s00521-022-07411-1
[Crossref]
11. Abbasi S, Rahmani AM, Balador A, Sahaϐi A (2023) A fault-tolerant adaptive genetic algorithm
for service scheduling in internet of vehicles. Appl Soft Comput 143:110413. https://doi.org/
10.1016/j.asoc.2023.110413
[Crossref]
12. Luo Q, Wang H, Zheng Y et al (2020) Research on path planning of mobile robot based on
improved ant colony algorithm. Neural Comput Applic 32:1555–1566. https://doi.org/10.
1007/s00521-019-04172-2
[Crossref]
13.Wu Z, Wu J, Zhao M et al (2021) Two-layered ant colony system to improve engraving robot’s
efϐiciency based on a large-scale TSP model. Neural Comput Applic 33:6939–6949. https://
doi.org/10.1007/s00521-020-05468-4
[Crossref]
14. Yu J, You X, Liu S (2022) Dynamically induced clustering ant colony algorithm based on a
coevolutionary chain. Knowl-Based Syst 251:109231. https://doi.org/10.1016/j.knosys.2022.
109231
[Crossref]
15. Shami TM, Mirjalili S, Al-Eryani Y et al (2023) Velocity pausing particle swarm optimization: a
novel variant for global optimization. Neural Comput Applic 35:9193–9223. https://doi.org/
10.1007/s00521-022-08179-0
[Crossref]
16. Kiruthiga D, Manikandan V (2023) Levy ϐlight-particle swarm optimization-assisted BiLSTM +
dropout deep learning model for short-term load forecasting. Neural Comput Applic 35:2679–
2700. https://doi.org/10.1007/s00521-022-07751-y
[Crossref]
17. Zhang X, Zhang X, Wu Z (2019) Spectrum allocation by wave based adaptive differential
evolution algorithm. Ad Hoc Netw 94:101969
[Crossref]
18. Kumar R, Kumar P, Kumar Y (2022) Three stage fusion for effective time series forecasting
using Bi-LSTM-ARIMA and improved DE-ABC algorithm. Neural Comput Applic 34:18421–
18437. https://doi.org/10.1007/s00521-022-07431-x
[Crossref]
19. Zhang X, Zhang X, Han L (2019) An energy efϐicient internet of things network using restart
artiϐicial bee colony and wireless power transfer. IEEE Access 7:12686–12695
[Crossref]
20. Stephan P, Stephan T, Kannan R et al (2021) A hybrid artiϐicial bee colony with whale
optimization algorithm for improved breast cancer diagnosis. Neural Comput Applic
33:13667–13691. https://doi.org/10.1007/s00521-021-05997-6
[Crossref]
21. Alrosan A, Alomoush W, Norwawi N et al (2021) An improved artiϐicial bee colony algorithm
based on mean best-guided approach for continuous optimization problems and real brain
MRI images segmentation. Neural Comput Applic 33:1671–1697. https://doi.org/10.1007/
s00521-020-05118-9
[Crossref]
22. Satoh T, Nishizawa S, Nagase J et al (2023) Artiϐicial bee colony algorithm-based design of
discrete-time stable unknown input estimator. Inf Sci 634:621–649. https://doi.org/10.1016/
j.ins.2023.03.130
[Crossref]
23.
Luo H, He C, Zhou J, Zhang L (2021) Rolling bearing sub-health recognition via extreme
learning machine based on deep belief network optimized by improved ϐireworks. IEEEAccess 9:42013–42026
[Crossref]
24. Han S, Zhu K, Zhou M et al (2022) A novel multiobjective ϐireworks algorithm and its
applications to imbalanced distance minimization problems. IEEE/CAA J Automatica Sinica
9(8):1476–1489
[Crossref]
25. Ma L, Cheng S, Shi Y (2021) Enhancing learning efϐiciency of brain storm optimization via
orthogonal learning design. IEEE Trans Syst Man Cybern Syst 51(1):6723–6742
[Crossref]
26. Xue Y, Zhao Y, Slowik A (2021) Classiϐication based on brain storm optimization with feature
selection. IEEE Access 9:16582–16590
27. Duan H, Zhao J, Deng Y, Shi Y, Ding X (2021) Dynamic discrete pigeon-inspired optimization
for multi-UAV cooperative search-attack mission planning. IEEE Trans Aerosp Electron Syst
57(1):706–720
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