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Ant Colony Optimization and Stochastic Gradient Descent

Nicolas Meuleau, Marco Dorigo
2002 Artificial Life  
In this paper, we study the relationship between the two techniques known as ant colony optimization (aco) and stochastic gradient descent.  ...  More precisely, we show that some empirical aco algorithms approximate stochastic gradient descent in the space of pheromones, and we propose an implementation of stochastic gradient descent that belongs  ...  The information provided is the sole responsibility of the authors and does not reflect the Community's opinion.  ... 
doi:10.1162/106454602320184202 pmid:12171633 fatcat:wtnytd2mgndmbocz5ui6os4npm

The Research of Wavelet Transform Blind Equalization Algorithm Based on Ant Colony Optimization

Lei Jinhui, Li Jingli
2014 International Journal of Control and Automation  
In optimizing and initializing equalizer weight vector, ACA can avoid falling into local extremum easily in Stochastic Gradient Descent Algorithm of CMA and improve the convergence speed and reduce the  ...  This paper mainly studies the ACA to initialize the equalizer weight vector and the theory of wavelet transform, comes up with the wavelet blind equalization algorithm based on Ant Colony Optimization  ...  This stochastic gradient descent algorithm is lack of global search ability.  ... 
doi:10.14257/ijca.2014.7.5.36 fatcat:c5glo2uhibdk7klmyhvkxhpbfe

Firefly Algorithm to Opmimal Distribution of Reactive Power Compensation Units

Vadim Z. Manusov, Pavel V. Matrenin, Lola S. Atabaeva
2018 International Journal of Electrical and Computer Engineering (IJECE)  
Comparison of gradient descent, Firefly algorithm and Firefly algorithm with gradient descent is carried out.  ...  Algorithms based on a bio-heuristic process can find a neighborhood of global extreme, so a local gradient descent in the neighborhood is applied for a more accurate solution of the problem.  ...  ACKNOWLEDGEMENTS The research was carried out under the State Assignment of the Ministry of Education and Science of the Russian Federation, Project 8.6809.2017/8.9.  ... 
doi:10.11591/ijece.v8i3.pp1758-1765 fatcat:5b2cgm7xcjeutmhdwai4fmybh4

An Efficient Solving the Travelling Salesman Problem : Global Optimization of Neural Networks by Using Hybrid Method [chapter]

Yong-hyun Cho
2010 Traveling Salesman Problem, Theory and Applications  
The global optimization method is a hybrid of a stochastic approximation (SA) (Styblinski & Tang, 1990 ) and a gradient descent method.  ...  Ant colony algorithms Ant-based algorithms are based on studies of ant colonies in nature (Dorigo et al., 1991; Dorigo & Gambardella, 1997) .  ...  This book is a collection of current research in the application of evolutionary algorithms and other optimal algorithms to solving the TSP problem.  ... 
doi:10.5772/12855 fatcat:tqwxnpwqcvatrbta3p6yjsafmy

Training neural networks with ant colony optimization algorithms for pattern classification

Michalis Mavrovouniotis, Shengxiang Yang
2014 Soft Computing - A Fusion of Foundations, Methodologies and Applications  
To address this issue, an ant colony optimization (ACO) algorithm is applied to train feed-forward neural networks for pattern classification in this paper.  ...  In addition, the ACO training algorithm is hybridized with gradient descent training.  ...  This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/K001310/1.  ... 
doi:10.1007/s00500-014-1334-5 fatcat:t3dzzhszardx3k7gb2aljx46d4

Optimal Fuzzy CLOS Guidance Law Design Using Ant Colony Optimization [chapter]

Hadi Nobahari, Seid H. Pourtakdoust
2005 Lecture Notes in Computer Science  
The well-known ant colony optimization meta-heuristic is applied to design a new command to line-of-sight guidance law.  ...  In this regard, the lately developed continuous ant colony system is used to optimize the parameters of a pre-constructed fuzzy sliding mode controller.  ...  Ant Colony Optimization Ant algorithms were inspired by the observation of real ant colonies.  ... 
doi:10.1007/11571155_10 fatcat:dkb55ronz5bbjdquwtiekfox4q

Role of Optimization Techniques in Engineering

Shikha Tripathi, Bharti B
2016 International Journal of Computer Applications  
Simulation of each case using MATLAB is done to prove the validity of optimized result and optimized designing.  ...  It is the result of continuous research that Optimization has been evolve into an established field and had expanded in many branches like linear conic optimization, convex optimization, global optimization  ...  For this an analogy has been given in between the parameters of ant colony and that of algorithm. Following table illustrate that fact.  ... 
doi:10.5120/ijca2016909846 fatcat:ndie4u5c6zfkxaqeelrdywzmxm

A Review of Heuristic Global Optimization Based Artificial Neural Network Training Approahes

D. Geraldine Bessie Amali, Dinakaran M.
2017 IAES International Journal of Artificial Intelligence (IJ-AI)  
This paper reviews the various heuristic global optimization algorithms used for training feedforward neural networks and recurrent neural networks.  ...  Training a neural network involves minimizing the mean square error between the target and network output. The error surface is nonconvex and highly multimodal.  ...  Ant colony optimization (ACO) is a global optimization algorithm that is inspired by the swarm behaviour of ants following a path seeking food from their colonies [28] .  ... 
doi:10.11591/ijai.v6.i1.pp26-32 fatcat:mkalw6ikzbh45fteocs56nuz4i

Advanced computer science and applications for soft computing of converged IT environments

Gangman Yi, Yi Pan
2018 Soft Computing - A Fusion of Foundations, Methodologies and Applications  
Many advanced computational methods have been successfully applied to a range of optimization and classification problems in soft computing, but there are still many practical problems tackled by traditional  ...  Submissions are welcomed on scientific programming applied to optimization in practical data.  ...  The gradient descent algorithm is called stochastic conjugate gradient descent based on mini-batch (SCGDM).  ... 
doi:10.1007/s00500-018-3522-1 fatcat:rxgu65h7fbhjbmty3uswajpd3y

A Survey of Optimization Methods from a Machine Learning Perspective [article]

Shiliang Sun, Zehui Cao, Han Zhu, Jing Zhao
2019 arXiv   pre-print
Finally, we explore and give some challenges and open problems for the optimization in machine learning.  ...  The systematic retrospect and summary of the optimization methods from the perspective of machine learning are of great significance, which can offer guidance for both developments of optimization and  ...  There are many types of heuristic optimization methods, including classical simulated annealing arithmetic, genetic algorithms, ant colony algorithms, and particle swarm optimization [158] , [159] ,  ... 
arXiv:1906.06821v2 fatcat:rcaas4ccpbdffhuvzcg2oryxr4

Simulated Annealing Algorithm for Deep Learning

L.M. Rasdi Rere, Mohamad Ivan Fanany, Aniati Murni Arymurthy
2015 Procedia Computer Science  
Some methods in training deep learning to make it optimal have been proposed, including Stochastic Gradient Descent, Conjugate Gradient, Hessian-free optimization, and Krylov Subspace Descent.  ...  This method can learn many levels of abstraction and representation to create a common sense of data such as text, sound and image. Although DL is useful for a variety of tasks, it's hard to train.  ...  Some examples of the successful methods for training of this technique are Stochastic Gradient Descent, Conjugate gradient, Hessian-free Optimization and Krylov Subspace Descent.  ... 
doi:10.1016/j.procs.2015.12.114 fatcat:sxqqvlroercmbkr3vpfmcg6req

Radial Basis Function Neural Network Model for Dissolved Oxygen Concentration Prediction Based on an Enhanced Clustering Algorithm and Adam

Dashe Li, Xueying Wang, Jiajun Sun, Yanli Feng
2021 IEEE Access  
ACKNOWLEDGMENT The authors would like to thank the editor-in-chief, the associate editor, and the reviewers for their insightful comments and suggestions.  ...  OVERALL OPTIMIZATION OF THE RBFNN The Adam algorithm [39] is different from traditional stochastic gradient descent [40] , [41] .  ...  In stochastic gradient descent, a single learning rate is used to update all weights, and the learning rate does not change during the training process.  ... 
doi:10.1109/access.2021.3066499 fatcat:asnahemvgna4fb7uicxwhtszyu

Images Boundary Extraction Based on Curve Evolution and Ant Colony Algorithm [chapter]

JinJiang Li, Da Yuan, Zhen Hua, Hui Fan
2010 Lecture Notes in Computer Science  
A new boundary contour extraction algorithm based on curve evolution model and ant colony algorithm is proposed in this paper.  ...  Firstly, ant colony algorithm is used to find the optima of snake points for rapidly converging near image edge.  ...  gradient descent iterative respectively.  ... 
doi:10.1007/978-3-642-13495-1_36 fatcat:pbjt2zjcc5c7dlkdyom4wdcbeq

An Improved ACOBP Algorithm for Load Forecasting in Power System

Meng-hua FAN
2017 DEStech Transactions on Engineering and Technology Research  
In this paper, a new ant colony algorithm is introduced and a new feedforward network training strategy, ACOBP algorithm, is proposed for the first time, based on the traditional linear feedforward neural  ...  network and BP algorithm.  ...  and adapt to the construction condition of ant colony algorithm.  ... 
doi:10.12783/dtetr/iceea2016/6726 fatcat:ggorrvnmejhz3bytoylihwug6e

Research on Thermal Error Compensation of Gear Hobbing Machine

Qianjian Guo, Shanshan Yu, Jianguo Yang
2013 Research Journal of Applied Sciences Engineering and Technology  
This study presents the whole process of thermal error modeling and compensation by using Back Propagation Network (BPN) and ant colony optimization is introduced into the training of BPN.  ...  The results show that the BPN model based on ant colony algorithm improves the prediction accuracy of thermal errors on the gear hobbing machine and the thermal drift has been reduced from 14.2 μm to 4.5  ...  ACKNOWLEDGMENT The authors gratefully acknowledge the financial support provided by the Project of Shandong Province Higher Educational Science and Technology Program (J11LD24) and the National Natural  ... 
doi:10.19026/rjaset.6.3950 fatcat:gax5pobyprhahodhh4q6scrc5q
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