检索结果-内蒙古大学图书馆

On the Use of evolutionary computation for In-Silico Medicine: Modelling Sepsis via Evolving Continuous Petri Nets 1

引用

22nd International Conference on Applications of evolutionary computation (EvoApplications) Held as Part of EvoStar Conference

作者： Hallawa, Ahmed Zechendorf, Elisabeth Song, Yi Schmeink, Anke Peine, Arne Marin, Lukas Ascheid, Gerd Dartmann, Guido Rhein Westfal TH Aachen Chair Integrated Signal Proc Syst D-52056 Aachen Germany Univ Hosp RWTH Aachen Dept Intens Care & Intermediate Care Aachen Germany Rhein Westfal TH Aachen Res Area Informat Theory & Systemat Design Commun D-52056 Aachen Germany Trier Univ Appl Sci Res Area Distributed Syst Trier Germany

ISBN: (数字)9783030166922

ISBN: (纸本)9783030166915;9783030166922

Sepsis is one of the leading causes of death in Intensive Care Units (ICU) world-wide. Continuous Petri Nets (CPNs) offer a promising solution in modelling its underlying complex pathophysiological processes. In this work, we propose a framework to evolve CPNs, i.e. evolve its places, transitions, arc weights, topology, and kinetics. This facilitates modeling complex biological systems, including activated signalling pathway in sepsis using limited experimental data. Inspired by Neuroevolution of Augmenting Topology (NEAT), which is adopted in Artificial Neural Networks (ANNs), our framework includes a genotype to phenotype mapping based on the CPN incidence matrix, and a fitness function, which considers both the behaviour of the evolving CPN and its emerging structural complexity. We tested our framework on ten different cases with different complexity structures. In the worst case, results show the NMSE less than 2% in the learning phase, and MSE of 13% in the validation phase. We applied our framework on real-world data from cell culture experiments, representing a biological pathway in sepsis. Using the output of these experiments, the proposed framework was able to evolve a CPN to model this pathway with an MSE value of 10% in the validation phase.

关键词： evolutionary computation Continuous Petri Nets Modelling sepsis Intensive care medicine

来源：评论

学校读者我要写书评

暂无评论

An implementation of evolutionary computation for path planning of cooperative mobile robots

An implementation of evolutionary computation for path plann...

引用

4th World Congress on Intelligent Control and Automation

作者： Zhong, Y Liang, JH Gu, GC Zhang, RB Yang, HY Harbin Engn Univ Comp Sci & Technol Coll Harbin Heilongjiang Pr Peoples R China

ISBN: (纸本)0780372689

This article describes how to apply Genetic Algorithm in finding a globally sub-optimal path for the robot group working under certain tasks. Path Planning is an important problem in robotics. With the development of Cooperative Robotics in the recent years, the problem of path planning for robot group is receiving more and more attentions and interests. In this paper, the problem of path planning for robot group is formalized as Multiple Travelling Salesman Problem(MTSP) that employed either Total-Path-Shortest or Longest-Path-Shortest as the evaluating criterion. Longest-Path-Shortest MTSP has never been studied before. The formalized models of the two kinds of Multiple Travelling Salesman Problem are presented in this paper, and the main idea and specific way of applying genetic algorithm in solving the two kinds of Travelling Salesman Problem or their admixture are also amply discussed in this paper. At the end the convergence analysis and the simulation are made, as the simulation result shows, it is an effective and robust way of solving the problem of path planning for robot group.

关键词： genetic algorithms path planning mobile robots cooperative systems multi-robot systems convergence evolutionary computation path planning cooperative mobile robots genetic algorithm globally sub-optimal path robot group multiple travelling salesman problem total-path-shortest longest-path-shortest convergence simulation

来源：评论

学校读者我要写书评

暂无评论

Towards evolutionary Multitasking: A New Paradigm in evolutionary computation

引用

2nd International Conference on computational Intelligence, Cyber Security and computational Models (ICC3)

作者： Ong, Yew-Soon Nanyang Technol Univ Sch Comp Engn Singapore 639798 Singapore

ISBN: (纸本)9789811002519;9789811002502

he design of population-based search algorithms of evolutionary computation (EC) has traditionally been focused on efficiently solving a single optimization task at a time. It is only very recently that a new paradigm in EC, namely, multifactorial optimization (MFO), has been introduced to explore the potential of evolutionary multitasking (Gupta A et al., IEEE Trans Evol Comput [1]). The nomenclature signifies a multitasking search involving multiple optimization tasks at once, with each task contributing a unique factor influencing the evolution of a single population of individuals. MFO is found to leverage the scope for implicit genetic transfer offered by the population in a simple and elegant manner, thereby opening doors to a plethora of new research opportunities in EC, dealing, in particular, with the exploitation of underlying synergies between seemingly unrelated tasks. A strong practical motivation for the paradigm is derived from the rapidly expanding popularity of cloud computing (CC) services. It is noted that CC characteristically provides an environment in which multiple jobs can be received from multiple users at the same time. Thus, assuming each job to correspond to some kind of optimization task, as may be the case in a cloud-based on-demand optimization service, the CC environment is expected to lend itself nicely to the unique features of MFO. In this talk, the formalization of the concept of MFO is first introduced. A fitness landscape-based approach towards understanding what is truly meant by there being underlying synergies (or what we term as genetic complementarities) between optimization tasks is then discussed. Accordingly, a synergy metric capable of quantifying the complementarily, which shall later be shown to act as a “qualitative” predictor of the success of multitasking is also presented (Gupta A et al., A study of genetic complementarity in evolutionary multitasking [2]). With the above in mind, a novel evolutionary algorithm (E

关键词： Multi-factorial optimization evolutionary computation Genetic complementarity

来源：评论

学校读者我要写书评

暂无评论

A Novel Pareto-VIKOR Index for Ranking Scientists' Publication Impacts: A Case Study on evolutionary computation Researchers

A Novel Pareto-VIKOR Index for Ranking Scientists' Publicati...

引用

IEEE Congress on evolutionary computation (IEEE CEC)

作者： Bidgoli, Azam Asilian Rahnamayan, Shahryar Mahdavi, Sedigheh Deb, Kalyanmoy UOIT Dept Elect Comp & Software Engn Nat Inspired Computat Intelligence NICI Lab Oshawa ON Canada Michigan State Univ Coin Lab Dept Elect & Comp Engn E Lansing MI 48824 USA

ISBN: (纸本)9781728121536

Scientists' publication impacts ranking is an important topic in scientometrics which is performed based on various proposed criteria. One of the well-known indicators is h-index which evaluates researchers achievements based on number of citations. The h-index has utilized in many research data sources because of its appropriate properties, but similar to other assessment indicators, it has own disadvantages. h-index cannot give a fair comparison between junior and senior researches. There are two reasons for this unfair comparison: (1) h-index depends on the research period of scholars and (2) the number of received citations can be increased by time, even if researcher doesn't publish new papers, the h-index increases. Consequently, in addition to h-index, the number of the years of academic research (called the research period) is preferable to be considered as an independent indicator, which makes us able to have a more fair evaluation. So these two objectives, maximizing h-index and minimizing research period, can be considered as a multi-criteria comparison task to assess researchers. In this paper, we propose a strategy based on Pareto dominance ranking which uses dominance concept to obtain an order for researchers. In order to complete ranking between scientists in the same rank, a multi-criteria decision making measure called VIKOR is utilized. Therefore, a total ranking measure (P-V index) is obtained using Perto front concept and VIKOR measure. The proposed method is applied on 235 researchers who are conducting research on evolutionary computation (EC) topic. The h-index value and the research period of scholars are collected via Google Scholar service. P-V index obtains 26 Pareto ranks for all researchers and places six EC scientists on the first Pareto front.

关键词： Scientometrics Researchers ranking Pareto-front Non-dominated sorting multi-criteria decision making h-index VIkor evolutionary computation P-V index

来源：评论

学校读者我要写书评

暂无评论

Rapid Antenna Prototyping Method by evolutionary computation and Inkjet Printing

Rapid Antenna Prototyping Method by Evolutionary Computation...

引用

IEEE MTT-S International Microwave Workshop Series on Advanced Materials and Processes for RF and THz Applications (IEEE MTT-S IMWS-AMP 2015)

作者： Shi, Xinyang Narusue, Yoshiaki Kawahara, Yoshihiro Asami, Tohru Univ Tokyo Grad Sch Informat Sci & Technol Bunkyo Ku 7-3-1 Hongo Tokyo Japan Japan Soc Promot Sci Chiyoda Ku Kojimachi Business Ctr Bldg5-3-1 Kojimachi Tokyo Japan JST PRESTO Dept Res Promot Chiyoda Ku Res Div Gobancho Bldg7 Gobancho Tokyo Japan

ISBN: (纸本)9781479964505

Antenna designs using evolutionary computation methods have been widely used because of the rapid development of wireless technologies. However, a large number of antennas must be analyzed when evolutionary computation methods are adopted. Running a simulation is the main method of obtaining information about an antenna, such as bandwidth and input impedance, but it is very time-consuming because complicated calculations are needed. In this paper, we proposed a method that quickly realizes optimization of structures of inkjet-printed antennas. We propose the use of inkjet technology to implement candidates generated by evolutionary computation methods and use the measurement results instead of complex calculations. This method also solves the problem in which the fitness of candidates is sometimes difficult to directly realize from simulations. This paper presents the optimization of an inkjet-printed antenna for energy harvesting from TV broadcast waves using the proposed technique and a genetic algorithm. An antenna in which the output voltage is 1.4 times that of a rectangular dipole was designed.

关键词： Antennas evolutionary computation fabrication

来源：评论

学校读者我要写书评

暂无评论

An evolutionary computation for supplier bidding strategy in electricity auction market

An evolutionary computation for supplier bidding strategy in...

引用

Winter Meeting of the IEEE-Power-Engineering-Society

作者： Xiong, GF Hashiyama, T Okuma, S Nagoya Univ Dept Elect Engn Nagoya Aichi 4648603 Japan

ISBN: (纸本)0780373227

The daily bidding strategy in a day-ahead electricity auction market is studied from a supplier's point of view. An improved evolution strategy is developed to evolve the bidding strategy and to maximize the supplier's profit in a long run. A perfectly competitive day-ahead electricity auction market, where no supplier posses the market power and all suppliers winning the market are paid on their own bids, is assumed here. The dynamic and the incomplete information of the market are emphasized. An agent based simulation method is presented in this paper. The simulation results show the feasibility of the proposed bidding strategy.

关键词： Deregulation day-ahead electricity auction market evolutionary computation supplier bidding strategy.

来源：评论

学校读者我要写书评

暂无评论

Creative AI Through evolutionary computation: Principles and Examples

引用

SN Computer Science 2021年第3期2卷 163页

作者： Miikkulainen, Risto The University of Texas at Austin and Cognizant Technology Solutions San Francisco United States

The main power of artificial intelligence is not in modeling what we already know, but in creating solutions that are new. Such solutions exist in extremely large, high-dimensional, and complex search spaces. Population-based search techniques, i.e. variants of evolutionary computation, are well suited to finding them. These techniques make it possible to find creative solutions to practical problems in the real world, making creative AI through evolutionary computation the likely “next deep learning.” © 2021, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. part of Springer Nature.

关键词： Decision making evolutionary computation Machine creativity Neuroevolution Real-world applications Surrogate modeling

来源：评论

学校读者我要写书评

暂无评论

EvoNF: A framework for optimization of fuzzy inference systems using neural network learning and evolutionary computation

EvoNF: A framework for optimization of fuzzy inference syste...

引用

IEEE International Symposium on Intelligent Control

作者： Abraham, A Monash Univ Sch Business Syst Clayton Vic 3168 Australia

ISBN: (纸本)078037620X

Several adaptation techniques have been investigated to optimize fuzzy inference systems. Neural network learning algorithms have been used to determine the parameters of fuzzy inference system. Such models are often called as integrated neuro-fuzzy models. In an integrated neuro-fuzzy model there is no guarantee that the neural network learning algorithm converges and the tuning of fuzzy inference system will be successful. Success of evolutionary search procedures for optimization of fuzzy inference system is well proven and established in many application areas. In this paper, we will explore how the optimization of fuzzy inference systems could be further improved using a meta-heuristic approach combining neural network learning and evolutionary computation. The proposed technique could be considered as a methodology to integrate neural networks, fuzzy inference systems and evolutionary search procedures. We present the theoretical frameworks and some experimental results to demonstrate the efficiency of the proposed technique.

关键词： fuzzy systems neural networks evolutionary computation hybrid system

来源：评论

学校读者我要写书评

暂无评论

DSO Contract Market for Demand Response Using evolutionary computation

DSO Contract Market for Demand Response Using Evolutionary C...

引用

IEEE Congress on evolutionary computation (IEEE CEC)

作者： Lacerda, Eduardo Lezama, Fernando Soares, Joao Vale, Zita Polytech Porto GECAD Porto Portugal Polytech Porto Porto Portugal

ISBN: (纸本)9781728183923

In this article, a cost optimization problem in local energy markets is analyzed considering fixed-term flexibility contracts between the DSO and aggregators. The DSO procures flexibility while aggregators of different types (e.g., conventional demand response or thermo-load aggregators) offer the service. We solve the proposed model using evolutionary algorithms based on the well-known differential evolution (DE). First, a parameter-tuning analysis is done to assess the impact of the DE parameters on the quality of solutions to the problem. Later, after finding the best set of parameters for the "tuned" DE strategies, we compare their performance with other self-adaptive parameter algorithms, namely the HyDE, HyDE-DF, and vortex search algorithms. Results show that with the identification of the best set of parameters to be used for each strategy, the tuned DE versions lead to better results than the other tested EAs. Overall, the algorithms are able to find near-optimal solutions to the problem and can be considered an alternative solver for more complex instances of the model.

关键词： demand response aggregator-DSO market differential evolution evolutionary computation

来源：评论

学校读者我要写书评

暂无评论

A Study on the Limitations of evolutionary computation and other Bio-inspired Approaches for Integer Factorization

A Study on the Limitations of Evolutionary Computation and o...

引用

International Conference on Soft Computing and Software Engineering (SCSE)

作者： Mishra, Mohit Gupta, Vaibhav Chaturvedi, Utkarsh Shukla, K. K. Yampolskiy, R. V. Indian Inst Technol BHU Varanasi Dept Comp Sci & Engn Varanasi 221005 Uttar Pradesh India Univ Louisville Dept Comp Engn & Comp Sci Louisville KY 40292 USA

Integer Factorization is a vital number theoretic problem frequently finding application in public-key cryptography like RSA encryption systems, and other areas like Fourier transform algorithm. The problem is computationally intractable because it is a one-way mathematical function. Due to its computational infeasibility, it is extremely hard to find the prime factors of a semi prime number generated from two randomly chosen similar sized prime numbers. There has been a recently growing interest in the community with regards to evolutionary computation and other alternative approaches to solving this problem as an optimization task. However, the results still seem to be very rudimentary in nature and there's much work to be done. This paper emphasizes on such approaches and presents a critic study in details. The paper puts forth criticism and ideas in this aspect. (C) 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://***/lienses/by-nc-nd/4.0). Peer-review under responsibility of organizing committee of the 7th Scientific-Technical Conference Material Problems in Civil Engineering

关键词： evolutionary computation Swarm Intelligence Integer Factorization

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：