检索结果-内蒙古大学图书馆

Music genre classification based on local feature selection using a self-adaptive harmony search algorithm

DATA & KNOWLEDGE ENGINEERING 2014年第Jul.期92卷 60-76页

作者： Huang, Yin-Fu Lin, Sheng-Min Wu, Huan-Yu Li, Yu-Siou Natl Yunlin Univ Sci & Technol Dept Comp Sci & Informat Engn Touliu 640 Yunlin Taiwan

This paper proposes an automatic music genre-classification system based on a local feature-selection strategy by using a self-adaptive harmony search (SAHS) algorithm. First, five acoustic characteristics (i.e., intensity, pitch, timbre, tonality, and rhythm) are extracted to generate an original feature set. A feature-selection model using the SAHS algorithm is then employed for each pair of genres, thereby deriving the corresponding local feature set. Finally, each one-against-one support vector machine (SVM) classifier is fed with the corresponding local feature set, and the majority voting method is used to classify each musical recording. Experiments on the GTZAN dataset were conducted, demonstrating that our method is effective. The results show that the local-selection strategies using wrapper and filter approaches ranked first and third in performance among all relevant methods. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Classification Information retrieval Feature selection harmony search algorithm

来源：评论

学校读者我要写书评

暂无评论

Optimum design of steel sway frames to BS5950 using harmony search algorithm

引用

JOURNAL OF CONSTRUCTIONAL STEEL REsearch 2009年第1期65卷 36-43页

作者： Saka, M. P. Middle E Tech Univ Dept Engn Sci TR-06531 Ankara Turkey

harmony search method based optimum design algorithm is presented for the steel sway frames. The harmony search method is a numerical optimization technique developed recently that imitates the musical performance process which takes place when a musician searches for a better state of harmony. Jazz improvisation seeks to find musically pleasing harmony similar to the optimum design process which seeks to find the optimum solution. The optimum design algorithm developed imposes the behavioral and performance constraints in accordance with BS5950. The member grouping is allowed so that the same section can be adopted for each group. The combined strength constraints considered for a beam-column take into account the lateral torsional buckling of the member. The algorithm presented selects the appropriate sections for beams and columns of the steel frame from the list of 64 Universal Beam sections and 32 Universal Column sections of the British Code. This selection is carried out so that the design limitations are satisfied and the weight of steel frame is the minimum. The number of design examples considered to demonstrate the efficiency of the algorithm is presented. (C) 2008 Elsevier Ltd. All rights reserved.

关键词： Optimum structural design Combinatorial optimization Stochastic search technique harmony search algorithm Minimum weight Steel frame

来源：评论

学校读者我要写书评

暂无评论

Hyperparameters optimization of convolutional neural network based on local autonomous competition harmony search algorithm

引用

JOURNAL OF COMPUTATIONAL DESIGN AND ENGINEERING 2023年第4期10卷 1280-1297页

作者： Liu, Dongmei Ouyang, Haibin Li, Steven Zhang, Chunliang Zhan, Zhi-Hui Guangzhou Univ Sch Mech & Elect Engn Guangzhou 510006 Peoples R China South China Univ Technol Sch Comp Sci & Engn Guangzhou 510006 Peoples R China RMIT Univ Grad Sch Business & Law Melbourne 3000 Australia

Because of the good performance of convolutional neural network (CNN), it has been extensively used in many fields, such as image, speech, text, etc. However, it is easily affected by hyperparameters. How to effectively configure hyperparameters at a reasonable time to improve the performance of CNNs has always been a complex problem. To solve this problem, this paper proposes a method to automatically optimize CNN hyperparameters based on the local autonomous competitive harmony search (LACHS) algorithm. To avoid the influence of complicated parameter adjustment of LACHS algorithm on its performance, a parameter dynamic adjustment strategy is adopted, which makes the pitch adjustment probability PAR and step factor BW dynamically adjust according to the actual situation. To strengthen the fine search of neighborhood space and reduce the possibility of falling into local optima for a long time, an autonomous decision-making search strategy based on the optimal state is designed. To help the algorithm jump out of the local fitting situation, this paper proposes a local competition mechanism to make the new sound competes with the worst harmonic progression of local selection. In addition, an evaluation function is proposed, which integrates the training times and recognition accuracy. To achieve the purpose of saving the calculation cost without affecting the search result, it makes the training time for each model depending on the learning rate and batch size. In order to prove the feasibility of LACHS algorithm in configuring CNN superparameters, the classification of the Fashion-MNIST dataset and CIFAR10 dataset is tested. The comparison is made between CNN based on empirical configuration and CNN based on classical algorithms to optimize hyperparameters automatically. The results show that the performance of CNN based on the LACHS algorithm has been improved effectively, so this algorithm has certain advantages in hyperparametric optimization. In addition, this p

关键词： harmony search algorithm convolutional neural network optimization speed hyperparameters optimization

来源：评论

学校读者我要写书评

暂无评论

A novel grouping harmony search algorithm for the multiple-type access node location problem

引用

EXPERT SYSTEMS WITH APPLICATIONS 2012年第5期39卷 5262-5270页

作者： Landa-Torres, I. Gil-Lopez, S. Salcedo-Sanz, S. Del Ser, J. Portilla-Figueras, J. A. Univ Alcala Dept Signal Theory & Commun Madrid 28871 Spain TECNALIA TELECOM Zamudio Bizkaia Spain

In this paper we present a novel grouping harmony search algorithm for the Access Node Location Problem (ANLP) with different types of concentrators. The ANLP is a NP-hard problem where a set of distributed terminals, with distinct rate demands, must be assigned to a variable number of concentrators subject to capacity constraints. We consider the possibility of choosing between different concentrator models is given in order to provide service demand at different cost. The ANLP is relevant in communication networks design, and has been considered before within the design of MPLS networks, for example. The approach we propose to tackle the ANLP problem consists of a hybrid Grouping harmony search (GHS) algorithm with a local search method and a technique for repairing unfeasible solutions. Moreover, the presented scheme also includes the adaptation of the GHS to a differential scheme, where each proposed harmony is obtained from the same harmony in the previous iteration. This differential scheme is perfectly adapted to the specifications of the ANLP problem, as it utilizes the grouping concept based on the proximity between nodes, instead of being only based on the grouping concept. This allows for a higher efficiency on the searching process of the algorithm. Extensive Monte Carlo simulations in synthetic instances show that this proposal provides faster convergence rate, less computational complexity and better statistical performance than alternative algorithms for the ANLP, such as grouping genetic algorithms, specially when the size of the scenario increases. We also include practical results for the application of GHS to a real wireless network deployment problem in Bizkaia, northern Spain. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： harmony search algorithm Access node location problem Grouping-based encoding Grouping genetic algorithms Hybrid algorithms

来源：评论

学校读者我要写书评

暂无评论

A multi-population harmony search algorithm with external archive for dynamic optimization problems

引用

INFORMATION SCIENCES 2014年 272卷 84-95页

作者： Turky, Ayad Mashaan Abdullah, Salwani Univ Kebangsaan Malaysia Ctr Artificial Intelligence Technol Data Min & Optimisat Res Grp Bangi 43600 Selangor Malaysia Swinburne Univ Technol Fac Informat & Commun Technol Hawthorn Vic 3122 Australia

Dynamic optimization problems present great challenges to the research community because their parameters are either revealed or changed during the course of an ongoing optimization process. These problems are more challenging than static problems in real-world applications because the latter are usually dynamic, with the environment constantly subjected to change or the size of a problem increasing sporadically. In solving dynamic optimization problems in the real world, proposed solutions should be able to monitor the movement of the optimal point and the changes in the landscape solutions. In this paper, a multi-population harmony search algorithm with external archive for dynamic optimization problems is proposed. harmony search algorithm is a population-based meta-heuristic optimization technique that is similar to a musical process when a musician is attempting to find a state of harmony. To tackle the problem of dynamism, the population of solutions is divided into several sub-populations such that each sub-population takes charge exploring or exploiting the search space. To enhance the algorithm performance further, an external archive is used to save the best solutions for later use. These solutions will then be used to replace redundant solutions in the harmony memory. The proposed algorithm is tested on the Moving Peak Benchmark. Empirical results show that the proposed algorithm produces better results than several of the current state-of-the-art algorithms. (C) 2014 Elsevier Inc. All rights reserved.

关键词： Multi-population harmony search algorithm Dynamic optimization problems External archive

来源：评论

学校读者我要写书评

暂无评论

Variance-Based harmony search algorithm for Unimodal and Multimodal Optimization Problems with Application to Clustering

引用

CYBERNETICS AND SYSTEMS 2014年第6期45卷 486-511页

作者： Kumar, Vijay Chhabra, Jitender Kumar Kumar, Dinesh JCDMCOE Comp Sci & Engn Dept Sirsa Haryana India Natl Inst Technol Dept Comp Engn Kurukshetra Haryana India GJUS&T Dept Comp Sci & Engn Hisar Haryana India

This article presents a novel variance-based harmony search algorithm (VHS) for solving optimization problems. VHS incorporates the concepts borrowed from the invasive weed optimization technique to improve the performance of the harmony search algorithm (HS). This eliminates the main problem of constant parameter setting in the algorithm proposed recently and named as explorative HS. It uses the variance of a current population as well as presents a solution vector to improvise the harmony memory. In addition, the dynamic pitch adjustment operator is used to avoid solution oscillation. The proposed algorithm is evaluated on 14 standard benchmark functions of various characteristics. The performance of the proposed algorithm is investigated and compared with classical HS, an improved version of HS, the global best HS, self-adaptive HS, explorative HS, and the recently proposed state-of-art gravitational search algorithm. Experimental results reveal that the proposed algorithm outperforms the above-mentioned approaches. The effects of scalability, noise, harmony memory size, and harmony memory consideration rate have also been investigated with the proposed algorithm. The proposed algorithm is then employed for a data clustering problem. Four real-life datasets selected from the UCI machine learning repository have been used. The results indicate that the VHS-based clustering outperforms the existing well-known clustering algorithms.

关键词： harmony search algorithm metaheuristics optimization

来源：评论

学校读者我要写书评

暂无评论

Parameter adaptive harmony search algorithm for unimodal and multimodal optimization problems

引用

JOURNAL OF COMPUTATIONAL SCIENCE 2014年第2期5卷 144-155页

作者： Kumar, Vijay Chhabra, Jitender Kumar Kumar, Dinesh JCDM Coll Engn CSE Dept Sirsa Haryana India Natl Inst Technol Dept Comp Engn Kurukshetra Haryana India GJUS&T Dept Comp Sci & Engn Hisar Haryana India

This paper presents a parameter adaptive harmony search algorithm (PAHS) for solving optimization problems. The two important parameters of harmony search algorithm namely harmony Memory Consideration Rate (HMCR) and Pitch Adjusting Rate (PAR), which were either kept constant or the PAR value was dynamically changed while still keeping HMCR fixed, as observed from literature, are both being allowed to change dynamically in this proposed PAHS. This change in the parameters has been done to get the global optimal solution. Four different cases of linear and exponential changes have been explored. The change has been allowed during the process of improvization. The proposed algorithm is evaluated on 15 standard benchmark functions of various characteristics. Its performance is investigated and compared with three existing harmony search algorithms. Experimental results reveal that proposed algorithm outperforms the existing approaches when applied to 15 benchmark functions. The effects of scalability, noise, and harmony memory size have also been investigated on four approaches of HS. The proposed algorithm is also employed for data clustering. Five real life datasets selected from UCI machine learning repository are used. The results show that, for data clustering, the proposed algorithm achieved results better than other algorithms. (C) 2013 Elsevier B.V. All rights reserved.

关键词： harmony search algorithm Optimization Metaheuristic Benchmark problems Data clustering

来源：评论

学校读者我要写书评

暂无评论

Offline Selective Harmonic Elimination With (2N+1) Output Voltage Levels in Modular Multilevel Converter Using a Differential harmony search algorithm

引用

IEEE ACCESS 2020年 8卷 121596-121610页

作者： Xin, Yayun Yi, Jin Zhang, Kai Chen, Canfeng Xiong, Jian Huazhong Univ Sci & Technol Sch Elect & Elect Engn Dept Appl Elect Engn Wuhan 430074 Peoples R China Natl Univ Singapore Environm Res Inst Singapore 119077 Singapore

(2N+1) selective harmonic elimination pulse-width modulation (SHE-PWM) is an effective switching strategy of the modular multilevel converter in medium-voltage cases. In these cases, the number of sub-modules (SMs) is not high. Compared to the traditional (N+1) SHE-PWM, (2N+1) SHE-PWM has N more voltage levels, thus it can yield much better harmonic performance. However, the task of selective harmonic elimination also becomes much more complicated since there are more switching angles to be determined. This paper proposes a differential harmony search algorithm (DHS) with a novel harmony improvisation procedure for solving this problem. The Bayesian optimization method is applied to find the optimal parameter configuration for DHS. The performance of DHS is compared with 6 other metaheuristic algorithms including differential evolution (DE), harmony search (HS), genetic algorithm (GA), particle swarm optimization (PSO), teaching and learning-based optimization (TLBO), and ant colony optimization (ACO). The comparison is conducted on a set of 100 (2N +1) SHE-PWM instances by varying the modulation index from 0.01 to 1.0 with a step of 0.01. The numerical results show that the proposed DHS outperforms other compared methods in terms of objective function values, algorithm robustness, the magnitude of fundamental harmonic, and the calculated total harmonic distortion values. The switching angles obtained by DHS are further validated by both Matlab/Simulink simulation and hardware experiment.

关键词： (2N+1) SHE-PWM modular multilevel converter harmony search algorithm

来源：评论

学校读者我要写书评

暂无评论

Forecasting Annual Power Generation Using a harmony search algorithm-Based Joint Parameters Optimization Combination Model

引用

ENERGIES 2012年第10期5卷 3948-3971页

作者： Sun, Wei Wang, Jingmin Chang, Hong N China Elect Power Univ Sch Econ & Management Baoding 071003 Hebei Peoples R China E China Univ Sci & Technol Minist Educ Key Lab Adv Control & Optimizat Chem Proc Shanghai 200237 Peoples R China

Accurate power generation forecasting provides the basis of decision making for electric power industry development plans, energy conservation and environmental protection. Since the power generation time series are rarely purely linear or nonlinear, no single forecasting model can identify the true data trends exactly in all situations. To combine forecasts from different models can reduce the model selection risk and effectively improve accuracy. In this paper, we propose a novel technique called the harmony search (HS) algorithm-based joint parameters optimization combination model. In this model, the single forecasting model adopts power function form with unfixed exponential parameters. The exponential parameters of the single model and the combination weights are called joint parameters which are optimized by the HS algorithm by optimizing the objective function. Real power generation time series data sets of China, Japan, Russian Federation and India were used as samples to examine the forecasting accuracy of the presented model. The forecasting performance was compared with four single models and four combination models, respectively. The MAPE of our presented model is the lowest, which shows that the proposed model outperforms other comparative ones. Especially, the proposed combination model could better fit significant turning points of power generation time series. We can conclude that the proposed model can obviously improve forecasting accuracy and it can treat nonlinear time series with fluctuations better than other single models or combination models.

关键词： power generation joint parameter optimization harmony search algorithm combination forecasting method

来源：评论

学校读者我要写书评

暂无评论

Robust eigenvalue placement optimization for high-order descriptor systems in a union region with disjoint discs based on harmony search algorithm

引用

NEURAL COMPUTING & APPLICATIONS 2017年第1-Sup期28卷 S1207-S1220页

作者： Zhai, Junchang Gao, Liqun Li, Steven Bohai Univ Coll Informat Sci & Technol Jinzhou 121013 Liaoning Peoples R China Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Liaoning Peoples R China RMIT Univ Grad Sch Business & Law Melbourne Vic 3000 Australia

In this paper, a new optimization scheme is proposed for robust eigenvalue placement in high-order descriptor systems in union region based on harmony search algorithm. The specification on the closed-loop eigenvalues is given in terms of robust union region stability constraints. The radius or the position of the subregions can be arbitrarily specified in complex plane for the transient performance request. By using exact eigenvalue placement theory and combining the harmony search algorithm, the robust eigenvalue placement for high-order descriptor linear system in union region is converted into a global dynamical optimization problem. Further, the eigenstructure of the closed-loop system matrix can be optimized with better robustness bound (i.e., the spectral upper bound of the maximum allowable perturbation or uncertainty for the system matrices) by the proposed scheme without imposing restriction on the differentiability of the nonlinear robust measure index function. Consequently, the robust feedback controller can be obtained by dynamically optimizing the eigenvalue and eigenvector pairs of the system. Finally, the simulation results illustrate the effectiveness and superiority of the proposed method.

关键词： harmony search algorithm Eigenvalue placement Optimization High-order descriptor systems First-order descriptor systems

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：