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evolutional algorithm based learning of time varying multipath fading channels for software defined radio

IEICE TRANSACTIONS ON COMMUNICATIONS 2006年第12期E89B卷 3269-3273页

作者： Mkrtchyan, Gagik Naito, Katsuhiro Mori, Kazuo Kobayashi, Hideo Mie Univ Grad Sch Engn Commun Lab Tsu Mie 5148507 Japan

Software defined radio, which uses reconfigurable signal processing devices, requires the determination of multiple unknown parameters to realize the potential capabilities of adaptive communication. evolutional algorithms are optimal multi dimensional search techniques, and are well known to be effective for parameter determination. This letter proposes an evolutional algorithm for learning the mobile time-varying channel parameters without any specific assumption of scattering distribution. The proposed method is very simple to realize, but can provide precise channel estimation results. Simulations of an OFDM system show that for an example of OFDM communication under the time-varying fading channel, the proposed learning method can achieve the better BER performance.

关键词： evolutional algorithms software-defined radio time-varying multipath fading channel dynamic learning systems

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Differential Evolutionary Optimization of an Equivalent Dipole Model for Electromagnetic Emission Analysis

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IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY 2018年第6期60卷 1635-1639页

作者： Zhao, Wei-Jiang Liu, En-Xiao Wang, Binfang Gao, Si-Ping Png, Ching Eng Agcy Sci Technol & Res Inst High Performance Comp Dept Elect & Photon Singapore 138632 Singapore Natl Univ Singapore NUSNNI NanoCore Singapore 117583 Singapore Natl Univ Singapore Dept Elect & Comp Engn Singapore 117583 Singapore

A near-field scanning based equivalent dipole model is introduced to simplify the analysis of the emission from an electronic component at its nearby receivers. The model consists of a set of infinitesimal magnetic dipoles, with the number, position, and moment of the dipoles being unknowns. A nonlinear optimization problem in terms of the unknown parameters is established through minimizing the difference between the magnitude of magnetic fields obtained by near-field scanning and the radiation from the equivalent dipoles. The problem is difficult to solve as the number of dipoles is unknown. A differential evolution method based global optimization algorithm is proposed to solve the problem. A set of subproblems is first derived. It is then solved sequentially one after the other by using the proposed algorithm. A combination of the obtained solutions forms a solution of the original optimization problem. Numerical results are presented to demonstrate the validity and efficiency of the proposed algorithm.

关键词： Emission equivalent dipole model evolutional algorithms near-field (NF) scanning optimization

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Multi-objective Parameter Optimization of a Series Hybrid Electric Vehicle Using Evolutionary algorithms

Multi-objective Parameter Optimization of a Series Hybrid El...

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5th IEEE Vehicle Power and Propulsion Conference (VPPC 09)

作者： Zhang, Bingzhan Chen, Zhihang Mi, Chris Murphey, Yi L. Hefei Univ Technol Sch Mech & Automot Engn 193 Tunxi Rd Hefei Peoples R China Univ Michigan Dept Elect & Comp Engn Dearborn MI 48128 USA

ISBN: (纸本)9781424426003

Hybrid powertrain control strategy and component sizing significantly affect vehicle performance, fuel economy and emissions in hybrid vehicles. Recent research activities in this field show that component sizing and the control strategy are quite intertwined in such a way that concurrent optimization of component sizing and control strategy is warranted. In this paper, we study the total optimization problem in a series HEV and apply evolutionary algorithms to the optimization problem. We will show through experiments that the proposed optimization method has the capability of providing a set of trade-off optimal solutions among the fuel economy and various emissions.

关键词： Hybrid Electric Vehicle Control Strategy multi-objective Optimization evolutional algorithms

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Genetically Evolved Extreme Learning Machine for Letter Recognition Dataset 9th

Genetically Evolved Extreme Learning Machine for Letter Reco...

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9th Annual International Conference of the Biologically-Inspired-Cognitive-Architectures-Society (BICA) on Biologically Inspired Cognitive Architectures (BICA) held as Part of the Joint Multi-Conference on Human-Level Artificial Intelligence (HLAI)

作者： Szandala, Tomasz Wroclaw Univ Sci & Technol Wroclaw Poland

ISBN: (纸本)9783319993164;9783319993157

It is well known that the performance of learning feed forward neural networks is in general far slower than required and it has been a major bottleneck in their applications. Two key obstacles the slow gradient-based learning algorithms which are extensively used to train neural networks. Combining slow training process with even slower evolutional methods appears to be incomprehensible but here comes the Extreme Learning Machine. ELM has randomly chosen hidden nodes and analytically determined only the output weights of network. In theory, this algorithm tends to provide good generalization performance at extremely fast learning speed. Experiment in this paper shows that ELM's classification efficiency can be noticeably improved if its training is combined with Genetic Algorithm.

关键词： Extreme Learning Machine Genetic algorithm Pattern recognition evolutional algorithms

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Evoluční optimalizace nákladní přepravy

Evoluční optimalizace nákladní přepravy

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作者： Beránek, Michal Brno University of Technology

Práce se zabývá problémem optimalizace nákladní přepravy. Cílem je minimalizace nákladů spojených s přepravou, které vyplývají z ujeté vzdálenosti.... 详细信息

Práce se zabývá problémem optimalizace nákladní přepravy. Cílem je minimalizace nákladů spojených s přepravou, které vyplývají z ujeté vzdálenosti. Při správném naplánování tras lze tyto náklady výrazně snížit, obzvlášť když se jedná o velký počet zákazníků, které je potřeba obsloužit. Tato práce se soustředí na řešení pomocí evolučních algoritmů, což jsou metody optimalizace založené na principech evoluce. Hlavní zaměření je na problém směrování vozidel s omezenou heterogenní flotilou vozidel. V práci je představeno několik evolučních algoritmů a jejich výsledky jsou porovnány. Nejlepší z nich, evoluční strategie používající lokální prohledávání blízkého okolí, dosahuje podobných, pro některé konkrétní úlohy i lepších výsledků, než jiné existující evoluční algoritmy, vytvořené pro řešení stanoveného problému.

关键词： Evoluční algoritmy optimalizace problém směrování vozidel heterogenní flotila omezená flotila evoluční strategie genetický algoritmus lokální prohledávání C++ HFVRP evolutional algorithms optimization vehicle routing problem heterogeneous fle

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Implementace evolučního expertního systému

Implementace evolučního expertního systému

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作者： Bukáček, Jan Brno University of Technology

Tato diplomová práce je zaměřena na nastudování problematiky evolučních a genetických algoritmů. A to především na multikriteriální algoritmy VEGA, SPEA a NSGA-II. Dá... 详细信息

Tato diplomová práce je zaměřena na nastudování problematiky evolučních a genetických algoritmů. A to především na multikriteriální algoritmy VEGA, SPEA a NSGA-II. Dále jednoho FrameWorku pracujícího s genetickými algoritmy a to jmenovitě WWW NIMBUS. Z uvedených algoritmů je vybrán algoritmus VEGA pro implementaci v jazyce JAVA na předem zvolený problém. Tímto problémem je výběr sloupů kvádrového profilu podle předem stanovených kritérií. Vybraný algoritmus pracuje na principu rozdělení populace do několika skupin a každou takto vzniklou skupinu ohodnotí fitness funkcí. Následuje ukázka implementace tohoto algoritmu. Dále je zde ukázka práce s FrameWorkem. V další části jsou srovnány výsledky vytvořeného programu s výsledky, které byly získány pomocí FrameWorku WWW NIMBUS. Jak pro VEGA, tak pro NIMBUS jsou zde ukázány jednotlivé výsledky. U VEGA je předveden i vývoj jednotlivých fitness funkcí. Také jsou zde ukázány grafy, které je možné získat pomocí NIMBUS. Na konci je uvedeno porovnání výsledků a navržení možných vylepšení.

关键词： Evoluení algoritmy Genetické algoritmy Multi-ktiteriální algoritmy FrameWork VEGA SPEA NSGA-II NIMBUS mutace křížení JAVA Eclipse. evolutional algorithms Genetic algorithms Multi-objective algorithms FrameWork VEGA SPEA NSGA-II NIMBUS

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Determination of canonical Huffman codeword lengths by evolution strategies

JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GA...

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JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY 2023年第2期38卷 771-780页

作者： Oral, Mustafa Assik, M. Mustafa Cukurova Univ Fac Engn Dept Comp Engn TR-01330 Adana Turkiye

Huffman coding is widely used in data compression. Canonical Huffman coding is a subset of Huffman coding and has some advantages, such as shorter header and less memory usage. Therefore, studies on this coding have been continuing. The algorithm producing the lengths of Algebraic Canonical Huffman Codes (ACHC) is one of these studies and this algorithm obtains the code lengths nearest to optimum value. In this study, an algorithm obtaining the code lengths that are the basis for the production of canonical Huffman codes using Evolutionary Strategies (ESs) is proposed, and this algorithm means that the ACHC algorithm is optimized by the ESs method. ESs is an evolutionary algorithm that mostly uses the mutation. Replication creates many copies of a single ancestor. The copies are mutated to produce offspring. Among the offspring and the ancestor, the individual with the best fitness value is chosen as the ancestor of the next generation. This cycle continues until the stop criteria is met. In this study, the length array obtained by ACHC was used as the first ancestor. The optimum value was achieved as a result of the evolution of this ancestor by mutation. As a result of the tests, the required number of cycles to reach the optimum value was determined as a fixed number. In this case, the time complexity is O (n2), where n is the number of symbols used. The amount of memory used is O (n2) because of the usage of multiple individuals.

关键词： Data Compression Canonical Huffman evolutional algorithms Evolution Strategies

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IMPROVED PARALLEL UNIVERSES ALGORITHM: AN EVOLUTIONARY ALGORITHM FOR COMBINATORIAL OPTIMIZATION

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INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING-THEORY APPLICATIONS AND PRACTICE 2020年第4期27卷 568-584页

作者： Bayat, Alireza Akbari Didehvar, Farzad Amirkabir Univ Technol Dept Math & Comp Sci Tehran Iran

This paper presents a basic approach to parallel universes algorithm (PU), and also a new version of PU. The new version is called the improved parallel universes (IPU) algorithm and is based on focusing on the solutions with a higher probability of improvement and two other strategies. These changes caused the IPU algorithm speed and optimality beyond what is achieved by the PU algorithm. The efficiency of the IPU algorithm is evaluated with the test function. Also, to take a closer look at the ability of the proposed algorithm, its performance is studied in the "capacitated vehicle routing problem" (CVRP) and "hybrid flow shop scheduling problem" (HFS), these two problems are selected because of their different structures. The results of the proposed algorithm on these two problems are compared with the results of several metaheuristic algorithms and the results indicate that the proposed algorithm is able to compete with other metaheuristic algorithms.

关键词： Metaheuristic evolutional algorithms parallel universes algorithm capacitated vehicle routing problem hybrid flow shop scheduling problem

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Combined heat and power economic dispatch using an adaptive cuckoo search with differential evolution mutation

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APPLIED ENERGY 2022年 307卷 118057-118057页

作者： Yang, Qiangda Liu, Peng Zhang, Jie Dong, Ning Northeastern Univ Sch Met Shenyang 110819 Peoples R China Newcastle Univ Sch Engn Merz Court Newcastle Upon Tyne NE1 7RU Tyne & Wear England

In power system operation, the combined heat and power economic dispatch (CHPED) is an attractive and momentous optimization problem where the major objective is to find an optimal generation schedule of heat and power to meet the heat and power demands with the minimum cost, while satisfying various practical operation constraints. This paper puts forward an adaptive cuckoo search with differential evolution mutation (ACS-DEM) for solving the CHPED problem. Compared with the basic cuckoo search (CS), there are three main improvements in the proposed ACS-DEM. The first improvement is that adaptive parameters are employed and therefore no parameter adjustment is required. The second is the incorporation of a Gaussian sampling strategy into the global search phase of the algorithm to increase the exploration capability. The third is the introduction of an improved differential evolution mutation strategy into the local search phase to replace the simple biased random walk in the basic CS, thus discouraging the blindness and enhancing the exploitation capability. The outstanding performance of ACS-DEM is first confirmed through the test suite from the 2017 Conference on Evolutionary Computation and then demonstrated on several CHPED problems. The obtained dispatch schedules from ACS-DEM are feasible and in most cases exhibit a distinct improvement over the results offered by six other CS-based algorithms, one state-of-the-art differential evolution algorithm, as well as recent works in this field.

关键词： Combined heat and power Economic energy dispatch Cuckoo search evolutional algorithms Optimization

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CONSTRUCTION OF MASTER RECESSION CURVE USING GENETIC algorithms

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JOURNAL OF HYDROLOGY AND HYDROMECHANICS 2012年第1期60卷 3-15页

作者： Gregor, Milos Malik, Peter Geol Survey Slovak Republ State Geol Inst Dionyz Stur Dept Hydrogeol & Geothermal Energy Bratislava 81704 Slovakia Comenius Univ Fac Nat Sci Dept Hydrogeol Bratislava 84215 Slovakia

The article describes a new methodology of using genetic algorithms to assemble a natural time series of discharge recession, from which a master recession curve can be interpreted both for streams and for springs. Presented approach can avoid obstacles such as limited time-series datasets, incomplete recessions or too many recessionary segments in many recession series, different time intervals of observations (daily or weekly frequencies). Short time series intervals, imprecise or mistaken measurements and different types of datasets (averaged or directly measured data) are taken into account as well. Even rough measurements of discharges with inaccurate sensing range can be analysed, if sufficiently long observation is available. Complicated hydrograph shapes in the case of e.g. karstic springs (often caused by combination of laminar and turbulent discharge sub-regimes due to karst network settings) can be processed as well. Subsequent construction of master recession curve is much easier an offers better conditions for its interpretation. Presented algorithm was already implemented to a programme solution, completed on the user form.

关键词： Recession Analysis Master Recession Curve Hybrid Genetic algorithms evolutional algorithms HydroOffice

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