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Integrated Speaker and Speech Recognition for Wheel Chair Movement using artificial Intelligence

INFORMATICA-JOURNAL OF COMPUTING AND INFORMATICS 2018年第4期42卷 587-594页

作者： Kaur, Gurpreet Srivastava, Mohit Kumar, Amod IK Gujral Punjab Tech Univ Kapurthala 144603 India Panjab Univ Univ Inst Engn & Technol Chandigarh 160025 India Chandigarh Engn Coll Landran 140307 Mohali India Cent Sci Instruments Org Chandigarh 160030 India

A speech signal is a result of the constrictions of vocal tract and different sounds can be generated by different vocal tract constrictions. A speech signal carries two things i.e. speaker's identity and meaning. For a specific applications of speaker and speech recognition like voice operated wheel chair, both the speaker and speech is to be recognized for movement of wheel chair. Automation in wheelchair is, today's requirement as the numbers of people are increasing with disabilities like injuries in spine, amputation, impairments in hands etc. They need assistance for moving their wheel chair. Voice operated wheel chair is one of the solution. The intention of this study is to use a speaker and speech dependent system to control the wheelchair and minimize the risk of unwanted accident. We have proposed a system in which speaker (patient) as well as speech (commands) is recognized based upon the acoustic features like Mel Frequency Cepstral Coefficients (MFCC). Optimization of the features using artificial bee algorithm (ABC) is done to gain good accuracy with artificial intelligence technique as a classifier. We have tested our system on standard dataset (TIDIGITS) and our own prepared dataset. Also, validation of proposed work is done by generating control signal to actuate the wheel chair in real time scenario.

关键词： speaker recognition speech recognition mel frequency cepstral coefficients artificial bee colony algorithm feed forward back propagation neural network

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Interval Type-2 Neural Fuzzy Controller-Based Navigation of Cooperative Load-Carrying Mobile Robots in Unknown Environments

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SENSORS 2018年第12期18卷 4181-4181页

作者： Lin, Chun-Hui Wang, Shyh-Hau Lin, Cheng-Jian Nation Cheng Kung Univ Dept Comp Sci & Informat Engn Tainan 701 Taiwan Natl Chin Yi Univ Technol Dept Comp Sci & Informat Engn Taichung 411 Taiwan

In this paper, a navigation method is proposed for cooperative load-carrying mobile robots. The behavior mode manager is used efficaciously in the navigation control method to switch between two behavior modes, wall-following mode (WFM) and goal-oriented mode (GOM), according to various environmental conditions. Additionally, an interval type-2 neural fuzzy controller based on dynamic group artificial bee colony (DGABC) is proposed in this paper. Reinforcement learning was used to develop the WFM adaptively. First, a single robot is trained to learn the WFM. Then, this control method is implemented for cooperative load-carrying mobile robots. In WFM learning, the proposed DGABC performs better than the original artificial bee colony algorithm and other improved algorithms. Furthermore, the results of cooperative load-carrying navigation control tests demonstrate that the proposed cooperative load-carrying method and the navigation method can enable the robots to carry the task item to the goal and complete the navigation mission efficiently.

关键词： evolutionary robot navigation control fuzzy control wall-following control cooperative carrying interval type-2 neural fuzzy controller artificial bee colony algorithm grouping strategy

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Evaluation of equipment maintenance quality: A hybrid multi-criteria decision-making approach

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ADVANCES IN MECHANICAL ENGINEERING 2019年第3期11卷

作者： Zhang, Libin Zhang, Lele Shan, Hongying Jilin Univ Transportat Coll Changchun Jilin Peoples R China Jilin Univ Sch Mech Sci & Engn Changchun 130022 Jilin Peoples R China

Maintenance plays a crucial role in the entire life cycle of equipment. With the acceleration of industrialization, the evaluation of equipment maintenance quality has undoubtedly become more challenging due to the complex mechanical structure, various maintenance modes, and so on. In order to make decisions scientifically, a hybrid multi-criteria decision-making approach integrating triangle fuzzy number, lambda-fuzzy measure, TOPSIS, and Choquet fuzzy integral is proposed in this article. First, the interaction among criteria can be handled reasonably by fuzzy integral based on lambda-fuzzy-measure. Second, fuzzy numbers which are given by experts are applied to deal with fuzzy linguistic value. In addition, artificial bee colony algorithm is first introduced to identify lambda-fuzzy-measure. The comparison results of three optimization algorithms which include artificial bee colony algorithm, genetic algorithm, and particle swarm optimization prove artificial bee colony algorithm is more effective than genetic algorithm and particle swarm optimization. A case study which contains six maintenance alternatives is practiced to prove the effectiveness of the proposed hybrid multi-criteria decision-making approach. Finally, the comparison is made between the proposed method and two classical multi-criteria decision-making approaches which refer to TOPSIS and gray correlation, and the results demonstrate the proposed method is suitable to solve maintenance quality evaluation problem.

关键词： Maintenance quality fuzzy number lambda-fuzzy measure Choquet fuzzy integral artificial bee colony algorithm TOPSIS multi-criteria decision-making approach optimization

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Study on the Rolling Schedule Optimization of Five Tandem Cold Rolling Mills 11

Study on the Rolling Schedule Optimization of Five Tandem Co...

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11th World Congress on Intelligent Control and Automation

作者： Wei, Lixin Lv, Bai Li, Ying Yang, Jingming Yanshan Univ Key Lab Ind Comp Control Engn Qinhuangdao Hebei Peoples R China

ISBN: (纸本)9781479958252

artificial bee colony (ABC) algorithm is a swarm intelligence optimization algorithm based on the working mechanism of honeybee swarms. It has advantages of less control parameters, easily programming and simple calculation, but there are still many problems to be improved and solved. Firstly, the logistic sequence to contro1 the mutation size is applied to improve the diversity of the population. Secondly several selection strategies are analyzed and compared through simulation. Results indicate that the improved algorithm performance was superior to the basic artificial bee colony algorithm. Finally, a modified artificial bee colony algorithm for rolling schedule was to code and operate the reduction rates by the targets of load equalization and rolling force equilibrium on certain constraint conditions. The practice on 5 stands tandem cold rolling mills shows that the rolling schedule makes the distribution of power and roll force reasonable, and increase economic benefit.

关键词： artificial bee colony algorithm tandem cold rolling self-adapting search space chaos sequence

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ABC-DE-WOA: A New Hybrid algorithm for Optimization Problems

ABC-DE-WOA: A New Hybrid Algorithm for Optimization Problems

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International Conference on Circuits, Communication, Control and Computing

作者： Pradeep Kumar D Sowmya BJ Anita Kanavalli Annvin Vincent Dept. of Computer Science and Engineering M S Ramaiah Institute of Technology (Affliaited to VTU) Bangalore Dept. of Artificial Intelligence and Data Science M S Ramaiah Institute of Technology (Affliaited to VTU) Bangalore

One of the most effective swarm intelligence-based algorithms for many global optimization issues is the artificial bee colony (ABC) strategy. Despite the fact that there are many artificial bee colony (ABC) variants, the algorithm normally has a low convergence rate. Therefore, it is still essential to moderate an algorithm's intensity and diversity. In this instance, the standard artificial bee colony (ABC) algorithm has been combined with the Whale Optimization algorithm (WOA) and Differential Evolution algorithm (DE) to generate a novel Hybrid artificial bee colony algorithm (ABC), artificial bee colony-Differential Evolution-Whale Optimization algorithm (ABC-DE-WOA). For simple benchmark problems with up to 100 dimensions, 50 dimensions, 30 dimensions, and 10 dimensions, the proposed hybrid technique is compared with artificial bee colony (ABC) variants like artificial bee colony-Whale Optimization algorithm (ABC-WOA), artificial bee colony-Differential Evolution algorithm (ABC-DE), and original artificial bee colony algorithm (ABC). The results show that the proposed technique performs better than its competitors in terms of convergence speed.

关键词： Benchmark testing artificial bee colony algorithm Whale optimization algorithms Hybrid power systems Optimization Standards Convergence

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Error Optimization in Random Number Generation Using ABC algorithm

Error Optimization in Random Number Generation Using ABC Alg...

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Modern Trends in Information and Communication Technology Industry (MTICTI), International Conference of

作者： Ghadir Alselwi Tuğrul TAŞCI Sakarya University Sakarya Turkey

ISBN: (纸本)9781665414456

Optimization is an effort to find the best option in the settings of the objective function. The goal of this study is to optimize multivariable functions using artificial bee colony (ABC) which is one of the most current swarm intelligence-based algorithms, simulating the foraging activity of honeybees. The performance of the ABC algorithm has been measured on the minimization process of 22 benchmark functions including the popular Griewank, Rastrigin, Sphere, and Rosenbrock. The experimental results demonstrate that the ABC algorithm has approximated the actual value with an accuracy percentage of 98.85.

关键词： Industries Current measurement artificial bee colony algorithm Minimization Market research Linear programming Information and communication technology

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Fractional-order control for nano-positioning of piezoelectric actuators

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INTERNATIONAL JOURNAL OF MODERN PHYSICS B 2022年第22期36卷 2250134-2250134页

作者： Yang, Liu Zhang, Yi Zhao, Zhongyang Li, Dongjie Harbin Univ Sci & Technol Sch Automat Harbin 150000 Peoples R China Key Lab Complex Intelligent Syst & Integrat Heil Harbin 150000 Peoples R China

Piezoelectric actuators are widely used in the field of high-precision positioning control. However, due to the inherent hysteresis nonlinearity of piezoelectric actuators, it can seriously affect their accuracy in tracking and positioning systems, and even cause system instability. In order to suppress the hysteresis characteristics of piezoelectric, based on the analysis of piezoelectric characteristics and the characteristics of classical Bouc- Wen model, a Bouc-Wen model is adopted to describe the hysteresis characteristics of piezoelectric actuators, an artificial bee colony (ABC) algorithm is used to identify Bouc-Wen. The maximum error of the model is 2.49%. According to the established hysteresis model, its inverse model is obtained as the feedforward controller, and the inverse model compensation method is used to realize the open-loop control of the system. Since the feedforward controller based on the inverse model cannot eliminate the modeling errors and external disturbances of the inverse model, a fractional-order controller is designed on the basis of inverse compensation, and a compound control method combining feedforward control and feedback control is adopted. Experiments show that the fractional-order control system has fast response speed, small steady-state error and simple structure compared with other nonlinear controllers, positioning error is about 3%.

关键词： Piezoelectric actuator hysteresis nonlinearity artificial bee colony algorithm fractional order (PID mu)-D-lambda micro-components

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An IABC Based Route Maintaining Protocol in Mobile Wireless Sensor Networks

An IABC Based Route Maintaining Protocol in Mobile Wireless ...

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2015 IEEE 16th International Conference on Communication Technology(ICCT 2015)

作者： Xiaoming Wu Yinglong Wang Yifan Hu College of Information Science and Engineering Shandong University of Science and Technology Shandong Computer Science Center (National Supercomputer Center in Jinan) Shandong Provincial Key Laboratory of Computer Networks

Recent studies have shown that utilizing a mobile sink to harvest and carry data from wireless sensor network(WSN) can enhance network operations and balance the network energy consumption. Because of the sink mobility, the paths between the sensor nodes and the sink change frequently, and have profound influence on the lifetime of WSN. To find an efficient protocol that can maintain the routes between the mobile sink and nodes with few network resources are important. We propose a swarm intelligent algorithm based route maintaining protocol in this paper to resolve this issue. The protocol utilizes the concentric ring mechanism to guide the route researching direction, and the optimal routing selection to maintain the data delivery route. Using the immune based artificial bee colony(IABC) algorithm to optimize the forwarding path,the protocol could find an alternative path efficiently when sink moves. The results of our experiments demonstrate that the protocol could balance the network traffic load.

关键词： Wireless sensor networks Mobile sink Route maintaining artificial bee colony algorithm Concentric ring

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Optimal Fast Charging Station Location for Public Electric Transportation in Smart Power Distribution Network

Optimal Fast Charging Station Location for Public Electric T...

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International Electrical Engineering Congress (iEECON)

作者： Terapong Boonraksa Boonruang Marungsri School of Electrical Engineering Suranaree University of Technology Nakhon Ratchasima Thailand

ISBN: (纸本)9781538623183;9781538623176

Electric vehicle (EV) become increasingly active in public transportation system. The battery and the charging system to keep it running are essential. For tech-economic benefits on the installation of the charging station, the location design is an important part. Include management to make it appropriate for the radial distribution system. This article presents an analysis to determine the optimal charging station for the radial distribution system. By simulating the charging station according to IEEE 33 bus standards. The artificial bee colony (ABC) algorithm is used to find the location of the best charging station for use with the radial distribution system. The results show that the proposed method finds the optimal charging station for EV. It can reduce the cost of creating additional locations including a suitable supply of the electrical system and it can also be applied to transportation systems within the city or between cities.

关键词： Charging stations Electric vehicles artificial bee colony algorithm Batteries Power distribution

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Adaptive Block-Based Compressed Sensing Based on Pre-sampling Using LDPC matrices

Adaptive Block-Based Compressed Sensing Based on Pre-samplin...

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Science and Technology Innovation (IAECST), International Academic Exchange Conference on

作者： Zhuyuan Xie Junkai Xia Mengjuan Ma School of Information Science and Engineering Yunnan University Kunming China

Assessing the sparsity of image blocks is the key of adaptive block-based compressed sensing (ABCS) algorithms. However, in practice, the digitized image cannot be directly obtained at the sampling device, therefore it is difficult to evaluate the sparsity of the original image. To solve this problem, two different measurement matrices are used in this paper. The original image is pre-sampled using binary low-density parity-check (LDPC) matrices, the sparsity of an image block is estimated by observing the pre-sampled measurement results, the total sampling rate is estimated according to the mean of the variances of the pre-sampled measurement results of all blocks. Then, a Gaussian random measurement matrix is used for the actual sampling. Experiment results show that, compared with the latest adaptive block-based compressed sensing methods, the proposed strategies have a significant improvement in peak signal-to-noise ratio (PSNR) at the same sampling rate, and it can also adaptively change the sampling rate according to the sparsity of the image.

关键词： Technological innovation PSNR Image coding artificial bee colony algorithm Parity check codes Sensors Compressed sensing

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