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International Conference On Smart Technologies For Smart Nation (SmartTechCon)

作者： Ravishankar, H. Patil, Kiran Kumari REVA Inst Technol & Management Comp Sci & Engn Bengaluru India REVA Univ Comp Sci & Engn Bengaluru India

ISBN: (纸本)9781538605691

The rapid growth of technology and smart phone industries has led to growth of wireless communication. Recent trends show that there is increasing in network traffic due to sharing of multimedia data such as VoIP (Voice over internet protocol), video conferencing, IPTV and so on. These services require strict QoS (Quality of Service) and network resources. To cater, new network protocol such as 4G and 5G is developed. However it induces high networkdeployment cost. The Wimax 802.16 network is currently adopted by all major service providers. Therefore the Wimax network has to provision policies and QoS for varied application. However, the WiMax does not provide implementation of these QoS policies for various application needs. Various scheduling mechanism has been developed in recent time for QoS provisioning. However these models are not efficient, due to improper synchronization of users. To develop an efficient QoS provisioning model by adopting evolutionary computing for finding ideal threshold, this work presents an uplink scheduling that minimize transmission error, buffer delay for low priority connection. The experiments are conducted to evaluate the performance of proposed model interm of throughput efficiency and slot utilization. The model achieves significant performance improvement over existing approach.

关键词： evolutionary computing IEEE 802.16 WiMAX Tactical network

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evolutionary computing applied to customer relationship management: A survey

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2016年 56卷 30-59页

作者： Krishna, Gutha Jaya Ravi, Vadlamani Inst Dev & Res Banking Technol Ctr Excellence Analyt Castle Hills Rd 1 Hyderabad 500057 Andhra Pradesh India Univ Hyderabad Sch Comp & Informat Sci Hyderabad 500046 Andhra Pradesh India

Customer relationship management (CRM) is a customer-centric business strategy which a company employs to improve customer experience and satisfaction by customizing products and services to customers' needs. This strategy, when implemented in totality eventually increases the revenue of the company. Traditionally, data mining (DM) techniques have been applied to solve various analytical CRM tasks. In turn, optimization techniques have long been used for training some of the DM techniques. However, during the past few years, evolutionary techniques have become so powerful and versatile that they can be deployed as a substitute for some DM techniques. This trend caught the attention of the researchers working in the analytical CRM area as they too started solving the CRM tasks using evolutionary techniques alone. In this context, we present a survey of evolutionary computing techniques applied to CRM tasks. In this paper, we surveyed 78 papers that were published during 1998 and 2015, where the application of evolutionary computing (EC) techniques to analytical CRM tasks is the main focus. The survey includes papers involving evolutionary computing techniques applied to the analytical CRM tasks under single-as well as multi-objective optimization framework. The purpose of the survey is to let the reader realize the versatility and power of EC techniques in solving analytical CRM tasks in the service industry and suggesting future directions. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Customer relationship management Data mining evolutionary computing Optimization

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The Concept of evolutionary computing for Robust Surgical Endoscope Tracking and Navigation

The Concept of Evolutionary Computing for Robust Surgical En...

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作者： Ying Wan University Of Technology Sydney

学位级别：博士

Navigated endoscopy is generally agreed to be the next generation of interventional or surgical endoscopy. It usually combines pre- and intra-operative imaging information to guide physicians during endoscopic procedures. However, endoscope three-dimensional motion tracking that spatially and temporally synchronizes various sensory information still remains challenging for developing different endoscopic navigation systems. To navigate or track the surgical endoscope, three modalities of sensory information are utilized in endoscopic procedures: (1) preoperative images, i. e., three-dimensional CT images, (2) two- dimensional video sequences from the endoscopic camera, and (3) location measurements, attaching an electromagnetic sensor at the endoscope distal tip for measuring the temporal endoscope movement. In this respect, endoscope tracking and navigation aims to fuse these various modalities information to accurately and robustly locate or fly through the endoscope at any interest of regions. Unfortunately, fusing the multimodal information is still an open issue due to the information incompleteness, e. g., image artifacts, tissue deformation, and sensor output inaccuracy in computer assisted endoscopic interventions. This thesis work focuses on fusing the multimodal information for accurate and robust endoscope tracking and navigation. A novel framework of multimodal information fusion is proposed to use evolutionary computing for endoscopic navigation systems. Several main contributions of this dissertation are clarified as follows. First, the concept of evolutionary computing was initially introduced to assist minimally invasive endoscopic surgery. Next, this work modified two evolutionary algorithms of particle swarm optimizer and differential evolution and proposed an enhanced particle swarm optimizer (EPSO) and observation- driven adaptive differential evolution (OADE). EPSO can adaptively update evolutionary parameters in accordance with spatial constrai

关键词： Minimally invasive surgery Bronchoscope Endoscopy Endoscopic navigation Endoscopic video processing Computer-assisted intervention 2D/3D registration Pre-and intra-operative imaging Electromagnetic tracking evolutionary computing Particle swarm optimizer Differential evolution

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Magnetic Design Optimization Approach Using Design of Experiments With evolutionary computing

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IEEE TRANSACTIONS ON MAGNETICS 2016年第3期52卷 1-4页

作者： Di Barba, P. Dughiero, F. Forzan, M. Sieni, E. Univ Pavia Dept Elect Comp & Biomed Engn I-27100 Pavia Italy Univ Padua Dept Ind Engn I-35131 Padua Italy

A new optimization method, combining design of experiments with evolutionary computing, is proposed. It handles a set of design variables, the size of which changes during the process. Initially, the most sensitive variables are activated;subsequently, the whole set of variables is activated. The optimal synthesis of a magnetic field for magnetofluid treatment is considered as the case study.

关键词： evolutionary computing finite elements (FEs) magnetic field synthesis multiobjective optimal design sensitivity analysis

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Human gait analysis based on biological motion and evolutionary computing

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ARTIFICIAL LIFE AND ROBOTICS 2016年第2期21卷 188-194页

作者： Sharma, Dipak G. Yusuf, Rahadian Tanev, Ivan Shimohara, Katsunori Doshisha Univ Kyotanabe Kyoto Japan

Human motion has already deeply affected many aspects of psychological and social research. On the other hand, because of the huge challenges and new dimensions of its increasingly extreme applications, this field remains an inspiring area in which to explore rich possibilities in the fields of artificial intelligence and bio-informatics. In this research, we investigated a novel approach to identify individuals based on their gaits. Furthermore, we investigated a new avenue of the research toward the biometric identification of humans that involves the classification of human gait using the power of genetic programming (GP). Moreover, we also propose an approach that applies collaborative filter using multiple evolved classifiers to address the challenges of non-determinism and insufficient generality of GP.

关键词： Collaborative filter evolutionary computing Genetic programming Human gaits Bio-informatics

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Outlier Detection using evolutionary computing 16

Outlier Detection using Evolutionary Computing

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1st International Conference on Informatics and Analytics (ICIA)

作者： Krishna, Gutha Jaya Ravi, Vadlamani Inst Dev & Res Banking Technol Ctr Excellence Analyt Castle Hills Rd 1 Hyderabad 500057 India Univ Hyderabad Sch CIS Prof CR Rao RdPO Cent Univ Hyderabad 500046 India

ISBN: (纸本)9781450347563

In this paper, we proposed Harmony Search and Differential Evolution based outlier detection for medium dimensional numerical datasets. The sparsity coefficient is taken as the objective function for finding outliers in the data. The upper limit of the number of dimensions for a dataset is fixed using the threshold suggested by Chebyshev's inequality. A t-test is conducted on the optimal sparsity coefficient for both methods over 30 simulations. At a 1% level of significance, the t-test confirmed that the Harmony Search based method is statistically more significant than Differential Evolution based one for all four datasets. Both methods outperformed the previous approaches.

关键词： evolutionary computing High Dimensional Data Outlier Detection

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Magnetic Design Optimization Approach Using Design of Experiments With evolutionary computing

Magnetic Design Optimization Approach Using Design of Experi...

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20th International Conference on the Computation of Electromagnetic Fields (Compumag)

作者： Di Barba, P. Dughiero, F. Forzan, M. Sieni, E. Univ Pavia Dept Elect Comp & Biomed Engn I-27100 Pavia Italy Univ Padua Dept Ind Engn I-35131 Padua Italy

关键词： evolutionary computing finite elements (FEs) magnetic field synthesis multiobjective optimal design sensitivity analysis

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evolutionary computing and Particle Filtering: A Hardware-Based Motion Estimation System

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IEEE TRANSACTIONS ON COMPUTERS 2015年第11期64卷 3140-3152页

作者： Rodriguez, Alfonso Moreno, Felix Univ Politecn Madrid Ctr Elect Ind ETSI Ind E-28006 Madrid Spain

Particle filters constitute themselves a highly powerful estimation tool, especially when dealing with non-linear non-Gaussian systems. However, traditional approaches present several limitations, which reduce significantly their performance. evolutionary algorithms, and more specifically their optimization capabilities, may be used in order to overcome particle-filtering weaknesses. In this paper, a novel FPGA-based particle filter that takes advantage of evolutionary computation in order to estimate motion patterns is presented. The evolutionary algorithm, which has been included inside the resampling stage, mitigates the known sample impoverishment phenomenon, very common in particle-filtering systems. In addition, a hybrid mutation technique using two different mutation operators, each of them with a specific purpose, is proposed in order to enhance estimation results and make a more robust system. Moreover, implementing the proposed evolutionary Particle Filter as a hardware accelerator has led to faster processing times than different software implementations of the same algorithm.

关键词： Embedded systems evolutionary computing FPGAs particle filtering

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Massively concurrent agent-based evolutionary computing

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JOURNAL OF COMPUTATIONAL SCIENCE 2015年第Nov.期11卷 153-162页

作者： Krzywicki, D. Turek, W. Byrski, A. Kisiel-Dorohinicki, M. AGH Univ Sci & Technol Fac Comp Sci Elect & Telecommun PL-30059 Krakow Poland

The fusion of the multi-agent paradigm with evolutionary computation yielded promising results in many optimization problems. evolutionary multi-agent systems (EMAS) are more similar to biological evolution than classical evolutionary algorithms. However, technological limitations prevented the use of fully asynchronous agents in previous EMAS implementations. In this paper we present a new algorithm for agent-based evolutionary computations. The individuals are represented as fully autonomous and asynchronous agents. An efficient implementation of this algorithm was possible through the use of modern technologies based on functional languages (namely Erlang and Scala), which natively support lightweight processes and asynchronous communication. Our experiments show that such an asynchronous approach is both faster and more efficient in solving common optimization problems. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Multi-agent systems evolutionary computing Functional programming

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Joint spectrum sensing for detection of primary users using cognitive relays with evolutionary computing

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IET COMMUNICATIONS 2015年第13期9卷 1643-1648页

作者： Salman, Ayesha Qureshi, Ijaz Mansoor Sultan, Kiran Saeed, Sarah Air Univ Dept Elect & Telecom Engn Islamabad 44000 Pakistan

The spectrum sensing is one of the most challenging research fields in cognitive radio networks (CRN). Joint spectrum sensing not only improves the detection performance of the system, but also increases overall agility of the CRN. This study presents a centralised relay-based spectrum sensing technique using hybrid nature based algorithm that detects the number of active primary users and jointly estimates (amplitude, carrier frequency and direction of arrival of far-field sources impinging on uniform linear arrays (ULA) mounted on each relay. The fitness function is a sum of mean square error and the correlation error. All the individual decisions from each relay are passed on to the fusion centre that provides the final decision on the values of the aforementioned parameters. The validity of the proposed scheme is investigated for various SNR levels along with different sizes of ULAs on each relay.

关键词： relay networks (telecommunication) cognitive radio radio spectrum management signal detection evolutionary computation array signal processing joint spectrum sensing primary user detection cognitive relays evolutionary computing CRN cognitive radio networks centralised relay-based spectrum sensing technique hybrid nature based algorithm uniform linear arrays ULA fitness function mean square error correlation error fusion centre

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