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Global Conference for Advancement in Technology (GCAT)

作者： Pooja Pol V. K. Pachghare Dept. of Computer Engineering & information Technology College of Engineering Pune India

ISBN: (纸本)9781728136950

Optimization is essential in every sector such as engineering design, economics, mathematics, physics, even in day to day activities such as holiday planning, internet usage/routing optimization is required. As resources such as money, resources and time are crucial and limited those needs to be used optimally always. This paper explains concept of optimization and classification of various optimization approaches, later it extends to meta-heuristic optimization algorithms, gives brief explanation about different swarm- based optimization algorithms. Optimization algorithms can be classified by many ways based on focus of algorithm utilization and characteristics. Metaheuristic approach mimics natural phenomena where nature is used as source of inspiration. This paper gives brief about all classifications of metaheuristic algorithms such as Evolutionary algorithms, swarm intelligence, differential evolution and hunting search algorithm which is the main focus of this paper. This paper explains Grey Wolf Optimization (GWO) in comparison of all other metaheuristic algorithms.

关键词： evolutionary computation particle swarm optimisation search problems evolutionary algorithm Particle swarm optimization tabu search virtues Optimization algorithms Taxonomy searching algorithm

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Massive Parallel Max-SAT Solver Based on Speculative Computation

Massive Parallel Max-SAT Solver Based on Speculative Computa...

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IIAI International Conference on Advanced Applied Informatics (IIAIAAI)

作者： Yasuki IIZUKA Haruki Koshiba Graduate School of Science Tokai University Hiratsuka Japan Dept. Mathematical Sciences Tokai University Hiratsuka Japan

ISBN: (纸本)9781728126289

This paper proposes a massive parallel Max-Sat solver based on speculative computation using GPUs. Max-SAT is a combinatorial optimization problem that maximizes the true clauses of the SAT clauses, and many Max-SAT solvers have been proposed. Parallelization is expected as an efficiency improvement method when solving problems with a large amount of computation such as Max-SAT. However, many of the Max-SAT solvers are designed as sequential programs, and the effect of parallelization is limited. In this study, we developed a massive parallel search algorithm by designing a parallel stochastic search algorithm and combining it with parallel speculative computation. From the comparison with existing solvers using the Max-SAT problem, we examine the feasibility of this method.

关键词： combinatorial mathematics computability optimisation search problems stochastic processes Speculative computing combinatorial mathematics tabu search computability Markov chain Solvers parallelization searching algorithm Parallel Lines Stochastic Processes

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AutoAugment: Learning Augmentation Strategies from Data

AutoAugment: Learning Augmentation Strategies from Data

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IEEE/CVF Conference on Computer Vision and Pattern Recognition

作者： Ekin D. Cubuk Barret Zoph Dandelion Mane Vijay Vasudevan Quoc V. Le Google Brain

ISBN: (纸本)9781728132945

Data augmentation is an effective technique for improving the accuracy of modern image classifiers. However, current data augmentation implementations are manually designed. In this paper, we describe a simple procedure called AutoAugment to automatically search for improved data augmentation policies. In our implementation, we have designed a search space where a policy consists of many sub-policies, one of which is randomly chosen for each image in each mini-batch. A sub-policy consists of two operations, each operation being an image processing function such as translation, rotation, or shearing, and the probabilities and magnitudes with which the functions are applied. We use a search algorithm to find the best policy such that the neural network yields the highest validation accuracy on a target dataset. Our method achieves state-of-the-art accuracy on CIFAR-10, CIFAR-100, SVHN, and ImageNet (without additional data). On ImageNet, we attain a Top-1 accuracy of 83.5% which is 0.4% better than the previous record of 83.1%. On CIFAR-10, we achieve an error rate of 1.5%, which is 0.6% better than the previous state-of-the-art. Augmentation policies we find are transferable between datasets. The policy learned on ImageNet transfers well to achieve significant improvements on other datasets, such as Oxford Flowers, Caltech-101, Oxford-IIT Pets, FGVC Aircraft, and Stanford Cars.

关键词： Policies searching algorithm Error analysis Dataset images Imagery (Psychotherapy) Shearing

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Proposing an Online Peer-Feedback Approach in Digital Game from A Semi-Puzzle Game-Based Learning Perspective

Proposing an Online Peer-Feedback Approach in Digital Game f...

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IIAI International Conference on Advanced Applied Informatics (IIAIAAI)

作者： Andang Adi Fitria Hananto Patcharin Panjaburee Institute for Innovative Learning Mahidol University Nakhon Pathom Thailand

ISBN: (纸本)9781728126289

With benefits of using educational games to support students learning performance and demands of digital game to assist searching algorithm learning, this study developed a semi-puzzle game called Key and Chest. To investigate the effectiveness of the developed game, a pilot study was conducted with eight high school students at a school in Thailand on a basic computer science course. The experimental results highlight that, in comparison with the physical game, the developed game helped them recognized searching concepts leading to improving their learning achievement. Moreover, the structured group interviews revealed that the developed game was mostly positive cognitive tool to support learning on the topic. In light of the previously mentioned, this paper extends and revises the developed game and addresses the application proposal with the use of online peer feedback mechanism to support collaborative learning in digital game-based learning environment on the searching algorithm topic.

关键词： computer aided instruction serious games (computing) computer-assisted instruction automatic game Hunting Game theory Game animals Experimental Games Learning Group Interviews Pilot Studies Students searching algorithm

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A New Frequency Detection Method Based on FFT in The Application of SAW Resonator Sensor 26

A New Frequency Detection Method Based on FFT in The Applica...

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26th Iranian Conference on Electrical Engineering (ICEE)

作者： Jazini, Mohammad Mahdi Khoshakhlagh, Mohammad Masoumi, Nasser Univ Tehran Coll Engn Sch ECE Dept ElectCST LAB Tehran *** Iran

ISBN: (纸本)9781538649169

Recognition of wireless and non-battery measurement systems makes passive surface acoustic wave (SAW) sensors valuable. The interrogation unit coordinates the SAW sensor system and provides the sensor's energy by transmitting pulse signals. The SAW sensor also transmits its response to the interrogation unit after being charged. The response signal of the SAW sensor is a noisy damped sine wave that should be received by the interrogation unit antenna. The received signal resonates at the SAW intrinsic frequency which changes with sensing characteristics. So the interrogation unit has the responsibility of detecting this damped sine wave frequency accurately and finding the exact value of the sensing parameter. Fast Fourier transform (FFT), zero crossing, and peak detection methods are used in most papers. However, after studying these methods, it is concluded that all of them have fundamental disadvantages namely inaccuracy and low speed. So by using estimation formulae, a new frequency detection method is designed based on FFT and used to compensate the drawbacks. Finally, the proposed method can help researchers to reduce the sampling frequency of the analog-to-digital converter (ADC) used in the interrogation unit. Also, the proposed method detects the initial phase and the amplitude of the response signal.

关键词： SAW sensor frequency detection method FFT zero crossing searching algorithm damped sine wave

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On the Exponential Number of Connected Components for the Feasible Set of Optimal Decentralized Control Problems

On the Exponential Number of Connected Components for the Fe...

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American Control Conference

作者： Han Feng Javad Lavaei Industrial Engineering and Operations Research University of California Berkeley

ISBN: (纸本)9781538679012;9781538679265

The optimal decentralized control (ODC) problem is known to be NP-hard and many sufficient tractability conditions have been derived in the literature for its convex reformulations or approximations. To better understand the root cause of the non-existence of efficient methods for solving ODC, we propose a measure of problem complexity in terms of connectivity, and show that there is no polynomial upper bound on the number of connected components for the set of static stabilizing decentralized controllers. Specifically, we present a subclass of problems for which the number of connected components is exponential in the order of the system and, in particular, any point in each of these components is the unique solution of the ODC problem for some quadratic objective functional. The results of this paper have two implications. First, the recent effort in machine learning advocating the use of local search algorithms for non-convex problems, which has also been successful for the optimal centralized control problem, fails to work for ODC since it needs an exponential number of initializations. Second, no reformulation of the problem through a smooth change of variables can reduce the complexity since it maintains the number of connected components. On the positive side, we show that structural assumptions can reduce the connectivity complexity of ODC, one such structure is the system being highly damped.

关键词： connected component searching algorithm decentralised control Exponential Instruction repertory ROOT CAUSES Non-Convex

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An Image Enhancement Optimization Method Based on Differential Evolution algorithm and Cuckoo Search Through Serial Coupled Mode

An Image Enhancement Optimization Method Based on Differenti...

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IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems

作者： Zhiwei Ye Ye Cao Aixin Zhang Can Jin Lie Ma Xiang Hu Jiwei Hu Hubei University of Technology Wuhan Jizhi Technology co. LTD Wuhan Fiberhome Technical Services Co. Ltd.

ISBN: (纸本)9781728140704

Image enhancement based on Beta function is a widely used method for it is able to fit multiple transformation curves, which is a significant step for image analysis. The key step for the method is to find the appropriate parameters to determine the grayscale transformation function. However, it needs a lot of time to seek applicable parameters when enumeration is used and random optimization algorithms often have failures within a limited time and are prone to fall into the local optimum. In order to solve the problems a serial coupled mode of stochastic optimization algorithms is investigated in the paper. According to the model, the differential evolution algorithm and cuckoo search algorithm are tried in image enhancement through serial coupling mode and compared with the traditional optimization algorithm. The experimental results reveals that the proposed approach is feasible and the performance is more balanced, which has a good performance on the image enhancement.

关键词： Image enhancement Hybrid algorithm Differential evolution algorithm Cuckoo search algorithm image enhancement differential evolution algorithms Optimization algorithms searching algorithm evolutionary algorithm Cuculidae Serial Publications BETA FUNCTIONS local optimum

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A Non-Deterministic Strategy for searching Optimal Number of Trees Hyperparameter in Random Forest

A Non-Deterministic Strategy for Searching Optimal Number of...

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Federated Conference on Computer Science and Information Systems

作者： Kennedy Senagi Nicolas Jouandeau Department of Information Technology Dedan Kimathi University of Technology LIASD University Paris8

ISBN: (纸本)9781538623718

In this paper, we present a non-deterministic strategy for searching for optimal number of trees hyperparameter in Random Forest (RF). Hyperparameter tuning in Machine Learning (ML) algorithms is essential. It optimizes predictability of an ML algorithm and/or improves computer resources utilization. However, hyperparameter tuning is a complex optimization task and time consuming. We set up experiments with the goal of maximizing predictability, minimizing number of trees and minimizing time of execution. Compared to the deterministic search algorithm, the non-deterministic search algorithm recorded an average percentage accuracy of approximately 98%, number of trees percentage average improvement of 44.64%, average time of execution mean improvement ratio of 175.62 and an average improvement of 94% iterations. Moreover, evaluations using Jackknife Estimation show stable and reliable results from several experiment runs of the non-deterministic strategy. The non-deterministic approach in searching hyperparameter shows a significant accuracy and better computer resources (i.e cpu and memory time) utilization. This approach can be adopted widely in hyperparameter tuning, and in conserving utilization of computer resources like green computing.

关键词： Hyperparameter searching algorithm optimum number trees Legal Executions central processing units

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Fault Diagnosis of Bearing by Utilizing LWT-SPSR-SVD-Based RVM with Binary Gravitational Search algorithm

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SHOCK AND VIBRATION 2018年第Pt.8期2018卷 8385021.1-8385021.8页

作者： Fei, Sheng-wei Donghua Univ Coll Mech Engn Shanghai 201620 Peoples R China

The fault diagnosis method of bearing based on lifting wavelet transform (LWT)-self-adaptive phase space reconstruction (SPSR)-singular value decomposition (SVD)-based relevance vector machine (RVM) with binary gravitational search algorithm (BGSA) is presented in this study, among which LWT-SPSR-SVD (LSS) is presented for feature extraction of the bearing vibration signal, the dynamic characteristics of lifting wavelet coefficients' (LWCs') reconstructed signals of the bearing vibration signal can be reflected by SPSR for LWCs' reconstructed signals of the bearing vibration signal, and BGSA is used to select the embedding space dimension and time delay of phase space reconstruction (PSR) and kernel parameter of RVM. In order to show the superiority of LWT-SPSR-SVD-based RVM with BGSA (LSS-BGSA-RVM), the traditional RVM trained by the training samples with the features based on LWT-SVD (LS-RVM) is used to compare with the proposed LSS-BGSA-RVM method. The experimental result demonstrates that compared with LS-RVM, LSS-BGSA-RVM can achieve the higher diagnosis accuracy for bearing.

关键词： Bearings diagnosis quality/standard Binary Phase space searching algorithm Fault diagnosis signals dynamic characteristics bearing vibration

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Cylindricity Error Evaluation Based on an Improved Harmony Search algorithm

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SCIENTIFIC PROGRAMMING 2018年第Pt.2期2018卷 13-13页

作者： Yang, Yang Li, Ming Wang, Chen Wei, QingYue Shanghai Univ Sch Mech Engn & Automat Key Lab Intelligent Mfg & Robot Shanghai 200072 Peoples R China Hubei Univ Automot Technol Dept Mech Engn Shiyan 442002 Peoples R China

The cylindricity error is one of the basic form errors in mechanical parts, which greatly influences the assembly accuracy and service life of relevant parts. For the minimum zone method (MZM) in international standards, there is no specific formula to calculate the cylindricity error. Therefore, the evaluation methods of the cylindricity error under the MZM have been widely concerned by international scholars. To improve the evaluation accuracy and accelerate the iteration speed of the cylindricity, an improved harmony search (IHS) algorithm is proposed and applied to compute the cylindricity. On the basis of the standard harmony search algorithm, the logistic chaotic initialization is introduced into the generation of initial solution to improve the quality of solutions. During the iterative process, the global and local search capabilities are balanced by adopting the par and bw operators adaptively. After each iteration, the Cauchy mutation strategy is adopted to the best solution to further improve the calculation precision of the IHS algorithm. Finally, four test functions and three groups of cylindricity error examples were applied to validity verification of the IHS algorithm, the simulation test results show that the IHS algorithm has advantages of the computing accuracy and iteration speed compared with other traditional algorithms, and it is very effective for the application in the evaluation of the cylindricity error.

关键词： Intelligent highway systems Cylindricity error searching algorithm MZM

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