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15th International Conference on Computational Collective Intelligence (ICCCI)

作者： Hollo-Szabo, Akos Botzheim, Janos Eotvos Lorand Univ Fac Informat Dept Artificial Intelligence Pazmany P Setany 1-A H-1117 Budapest Hungary

ISBN: (纸本)9783031417733;9783031417740

bacterial memetic algorithms (BMA) are a relatively new branch of evolutionary algorithms that are good alternatives to traditional genetic algorithms. They meant a significant breakthrough regarding order-based optimizations like the traveling salesman problem. In BMA the selection and mutation steps are replaced by bacterial mutation. During bacterial mutation each specimen of the population is improved separately by cloning them, mutating each clone, and then selecting one as a replacement for the original specimen. The bacterial mutation is one of the most innovative and critical steps of the BMA. bacterial mutations have many variants, but documentation lacks detailed statistics and behavior models. In this publication, we compare different bacterial mutation operators. The gathered data and observations will support all future research targeting BMA.

关键词： Traveling Salesman Problem bacterial memetic algorithm bacterial Mutation

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bacterial memetic algorithm Trained Fuzzy System-Based Model of Single Weld Bead Geometry

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IEEE ACCESS 2020年 8卷 164864-164881页

作者： Horvath, Csongor Mark Botzheim, Janos Thomessen, Trygve Korondi, Peter Budapest Univ Technol & Econ Dept Mechatron Opt & Mech Engn Informat Fac Mech Engn H-1111 Budapest Hungary PPM Robot AS N-7038 Trondheim Norway

This article presents a fuzzy system-based modeling approach to estimate the weld bead geometry (WBG) from the welding process variables (WPVs) and to achieve a specific weld bead shape. The bacterial memetic algorithm (BMA) is applied to solve these problems in two different roles, as a supervised trainer, and as an optimizer. As a supervised trainer, the BMA is applied to tune two different WBG models. The bead geometry properties (BGP) model follows a traditional approach providing the WBG properties as outputs. The direct profile measurement (DPM) model describes the bead profiles points by a non-linear function realized in the form of fuzzy rules. As an optimizer, the BMA utilizes the developed fuzzy systems to find the solution sets of WPVs to acquire the desired WBG. The best performance is achieved by applying six rules in the BGP model and eleven rules in the DPM model. The results indicate that the normalized root means square error for the validation data set lies in the range of 0.40 - 1.56% for the BGP model and 4.49 - 7.52% for the DPM model. The comparative analysis suggests that the BGP model estimates the BWG in a superior manner when several WPVs are altered. The developed fuzzy systems provide a tool for interpreting the effects of the WPVs. The developed optimizer provides multiple valid set of WPVs to produce the desired WBG, thus supporting the selection of those process variables in applications.

关键词： Welding Numerical models Microorganisms Geometry Shape memetics Fuzzy systems bacterial memetic algorithm fuzzy system machine learning TIG welding weld bead geometry

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bacterial memetic algorithm based Feature Selection for Surface EMG based Hand Motion Recognition in Long-term Use

Bacterial Memetic Algorithm based Feature Selection for Surf...

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IEEE Symposium Series on Computational Intelligence (IEEE SSCI)

作者： Zhou, Dalin Fang, Yinfeng Botzheim, Janos Kubota, Naoyuki Liu, Honghai Univ Portsmouth Intelligent Syst & Biomed Robot Grp Sch Comp Portsmouth PO1 3HE Hants England Tokyo Metropolitan Univ Grad Sch Syst Design 6-6 Asahigaoka Hino Tokyo 1910065 Japan

ISBN: (纸本)9781509042401

Pattern recognition algorithms have been applied in the surface electromyography (sEMG) based hand motion recognition for their promising accuracy. Research on proposing new features, improving classifiers and their combinations has been extensively conducted in the past decade. Meanwhile, the feature projection methodology, has been routinely exploited between the phases of feature extraction and classification. However, limited publications have been seen addressing the feature selection, which is a vital alternative in dimensionality reduction for pattern recognition. Recent development of sEMG acquisition devices have contributed to more signal capturing sites or even detection arrays of high density in the application. In this paper, the memetic evolutionary method named bacterial memetic algorithm (BMA) has been adopted as the feature selection strategy for sEMG based hand motion recognition. A case study of 4 subjects in long-term use has been conducted to demonstrate the feasibility of the proposed strategy, that comparable recognition accuracy with reduced computation cost has been achieved. A further discussion on the feature redundancy and inter-subject use has also been demonstrated based on the experimental results derived from BMA based feature selection.

关键词： Electromyography Hand Motion Pattern Recognition Feature Selection bacterial memetic algorithm

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bacterial memetic algorithm based Feature Selection for Surface EMG based Hand Motion Recognition in Long-term Use

Bacterial Memetic Algorithm based Feature Selection for Surf...

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IEEE Symposium Series on Computational Intelligence

作者： Dalin Zhou Yinfeng Fang János Botzheim Naoyuki Kubota Honghai Liu Intelligent Systems & Biomedical Robotics Group School of Computing University of Portsmouth PO1 3HE UK Graduate School of System Design Tokyo Metropolitan University 6-6 Asahigaoka Hino 191-0065 Japan

ISBN: (纸本)9781509042418

关键词： Electromyography Hand Motion Pattern Recognition Feature Selection bacterial memetic algorithm

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bacterial memetic algorithms for Order Picking Routing Problem with Loading Constraints

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EXPERT SYSTEMS WITH APPLICATIONS 2018年 105卷 196-220页

作者： Bodis, Tamas Botzheim, Janos Szechenyi Istvan Univ Dept Logist & Forwarding Egyet Ter 1 H-9026 Gyor Hungary Szechenyi Istvan Univ Dept Automat Egyet Ter 1 H-9026 Gyor Hungary

Order picking is the most labour and capital intensive warehousing operation whose primary development field is routing optimisation due to its time consuming nature. The Order Picking Routing Problem is a special case of the vehicle routing problem with loading constraints, when the operator visits picking positions and collects items to build transport unit. Where the stacking and stability challenges are relevant during the picking of ordered items and exact routing algorithms are not available, the order picking operators have huge challenges to sequence the order picking list. They should take into consideration several factors by themselves, such as product properties, order picking list characteristics, and order picking system properties. The goal of the proposed research is to support the order picking operators in order to make more objective decisions in decreasing the order picking lead time, building stable transport units, and avoiding product damages, when industrially relevant, but rarely discussed, order picking sequencing based on stacking property is necessary. The paper defines the Order Picking Routing Problem based on Pallet Loading Feature (OPRP-PLF) and presents bacterial memetic algorithm (BMA) based solutions for it, which is compared to Simulated Annealing (SA) algorithms. BMA has already been applied for Travelling Salesman Problem (TSP) but never used for the defined OPRP-PLF. The paper describes several BMA operators, most of them have an alternative which can be completed with SA based decisions. Using the BMA operators with SA methodology is a novelty of the proposed algorithms, which might support a quicker approximation to the global optimum. The possible combination of BMA operators will be evaluated with shorter and longer order picking lists and compared to SA algorithms on the same basis. The simulation results highlight, that allowing unit load reconstruction could decrease the order picking lead time and the developed BMA algo

关键词： Order picking Routing Pallet Loading bacterial memetic algorithm Simulated Annealing

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bacterial memetic algorithm for offline path planning of mobile robots

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memetic COMPUTING 2012年第1期4卷 73-86页

作者： Botzheim, Janos Toda, Yuichiro Kubota, Naoyuki Szechenyi Istvan Univ Dept Automat H-9026 Gyor Hungary Tokyo Metropolitan Univ Grad Sch Syst Design Hino Tokyo 1910065 Japan

The goal of the path planning problem is to determine an optimal collision-free path between a start and a target point for a mobile robot in an environment surrounded by obstacles. This problem belongs to the group of combinatorial optimization problems which are approached by modern optimization techniques such as evolutionary algorithms. In this paper the bacterial memetic algorithm is proposed for path planning of a mobile robot. The objective is to minimize the path length and the number of turns without colliding with an obstacle. The representation used in the paper fits well to the algorithm. memetic algorithms combine evolutionary algorithms with local search heuristics in order to speed up the evolutionary process. The bacterial memetic algorithm applies the bacterial operators instead of the genetic algorithm's crossover and mutation operator. One advantage of these operators is that they easily can handle individuals with different length. The method is able to generate a collision-free path for the robot even in complicated search spaces. The proposed algorithm is tested in real environment.

关键词： bacterial memetic algorithm Path planning

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Fuzzy rule-based model for outlier detection in a Topical Negative Pressure Wound Therapy Device

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ISA TRANSACTIONS 2021年 117卷 16-27页

作者： Phiri, Charles C. Valle, Cristina Botzheim, Janos Ju, Zhaojie Liu, Honghai CC Initiat Ltd Andover Hants England Univ Portsmouth Sch Comp Portsmouth Hants England Tokyo Metropolitan Univ Tokyo Japan Budapest Univ Technol & Econ Fac Mech Engn Dept Mechatron Opt & Mech Engn Informat Budapest Hungary

This paper proposes a novel method for offline outlier detection in nonlinear dynamical systems using an input-output dataset of a Topical Negative Pressure Wound Therapy Device, NPWT. The fundamental characteristics of an NPWT describe a chaotic system whose states vary over time and may result in unpredictable and possibly anomalous divergent behavior in the presence of perturbations and other unmodeled system dynamics, despite a quasi-stable controller. bacterial memetic algorithm, BMA, is used to generate fuzzy rule-based models of the input-output dataset. The error definition in the fuzzy rule extraction features a novel application of the Canberra Distance. The optimal number of rules for identifying the outliers, validated against both artificial and real system datasets, is calculated from the sample of inferred fuzzy models. The optimal number of rules is two in both cases based on the maximum average-error-drop. Using three or more rules results in better error performance;however, the algorithm learns the nuances of the outlier patterns instead. Novel methods for creating the outlier list and determining the optimal number of rules for the outlier detection problem are proposed. (C) 2021 ISA. Published by Elsevier Ltd. All rights reserved.

关键词： Topical Negative Pressure Wound Therapy Device Outlier detection Fuzzy rule-based model bacterial memetic algorithm

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Bead geometry modeling on uneven base metal surface by fuzzy systems for multi-pass welding

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EXPERT SYSTEMS WITH APPLICATIONS 2021年 186卷 115356-115356页

作者： Horvath, Csongor Mark Botzheim, Janos Thomessen, Trygve Korondi, Peter Budapest Univ Technol & Econ Fac Mech Engn Dept Mechatron Opt & Mech Engn Informat Muegyetem Rkp 3 H-1111 Budapest Hungary PPM Robot AS Leirfossvegen 27 N-7038 Trondheim Norway

This paper presents a modeling method of weld bead profiles deposited on uneven base metal surfaces and its application in multi-pass welding. The robotized multi-pass tungsten inert gas welding requires precise positioning of the weld beads to avoid welding defects and achieve the desirable welding join since the weld bead shapes depend on the surface of the previously deposited beads. The proposed model consists of fuzzy systems to estimate the coefficients of the profile function. The characteristic points of the trapezoidal membership functions in the rule bases are tuned by the bacterial memetic algorithm during supervised training. The fuzzy systems are structured as multiple-input-single-output systems, where the inputs are the welding process variables and the coefficients of the shape functions of the segments underlying the modeled bead;the outputs are the coefficients of the bead shape function. Each segment surface is approximated by a second-order polynomial function defined in the weld bead's local coordinate system. The model is developed from empirical data collected from single and multi-pass welding. The performance of the proposed model is compared with a multiple linear regression model. During the experimental validation, first, the individual beads are evaluated by comparing the estimated coefficients of the profile function and other bead characteristics (bead area, width, contact angles, and position of the toe points) with the measurements, and the estimations of a multiple linear regression model. Second, the sequential placement of the weld beads is evaluated while filling a straight Vgroove by comparing the estimated bead characteristics with the measurements and calculating the accumulated error of the filled groove cross-section. The results show that the proposed model provides a good estimation of the bead shapes during deposition on uneven base metal surfaces and outperforms the regression model with low error in both validation case

关键词： Multi-pass Welding Weld Bead Profile Modeling bacterial memetic algorithm Fuzzy Systems Machine Learning

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A Novel Diversity Induction Method for bacterial memetic algorithm by Hibernation of Individuals

A Novel Diversity Induction Method for Bacterial Memetic Alg...

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6th International Conference on Genetic and Evolutionary Computing (ICGEC)

作者： Botzheim, Janos Tokyo Metropolitan Univ Grad Sch Syst Design Hino Tokyo 1910065 Japan

ISBN: (纸本)9780769547633;9781467321389

memetic algorithms combine evolutionary algorithms with local search heuristics in order to speed up the evolutionary process. The bacterial memetic algorithm applies the bacterial operators instead of the genetic algorithm's crossover and mutation operator. In this paper a novel diversity induction method is proposed for bacterial memetic algorithm. Hibernation of some individuals in the population is applied for avoiding premature convergence to local optima. This operation can help in turning back from unpromising region of the search space by previously found solutions represented in hibernated bacteria.

关键词： memetic algorithm bacterial memetic algorithm diversity hibernation

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Multi-length Windowed Feature Selection for Surface EMG Based Hand Motion Recognition 11th

Multi-length Windowed Feature Selection for Surface EMG Base...

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11th International Conference on Intelligent Robotics and Applications (ICIRA)

作者： Zhou, Dalin Fang, Yinfeng Ju, Zhaojie Liu, Honghai Univ Portsmouth Sch Comp Intelligent Syst & Biomed Robot Grp Portsmouth PO1 3HE Hants England

ISBN: (纸本)9783319975863;9783319975856

Feature selection for surface electromyography based hand motion recognition has been seen to retrieve an optimal or quasi-optimal feature subset for classification. This work aims to consider the influence of channel, feature and window length simultaneously with an emphasis on the multiple segmentation. The bacterial memetic algorithm is applied to select the feature candidates from time domain and autoregressive coefficients, which is measured by the inter-day hand motion recognition accuracy. The evaluation is conducted on a case study of 3 able-bodied subjects performing 9 hand motions in consecutive 7 days with 4 different window lengths adopted for the electromyographic data segmentation. Classification in combination with the multi-length windowed feature selection achieved an improved recognition accuracy in comparison with using solely the single-length windowed features in inter-day scenarios and indicated that complementary information to full length segmentation resides in the sub-windows, thus providing feasible feature combinations for conventional pattern recognition based solutions to prosthetic control.

关键词： Electromyography Hand motion recognition Window segmentation Feature selection bacterial memetic algorithm

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