Pub Date : 2022-07-18DOI: 10.1109/COMPENG50184.2022.9905428
Jana Ihrens, Tim Schneider, T. A. Kern
Simulations are an important tool in the development of new direct current (DC) grids, as there are hardly any corresponding grids that can be used for testing. For the successful introduction of DC-grid technology, it is necessary to make a decision between risk-taking and system oversizing. Hence, simulations in this new domain have to validly represent reality, while keeping the demands on development time and computation time as low as possible. However, the necessary level of detail is often unclear and so far there is no methodology for balancing complexity and accuracy. Therefore, the initial analysis of complexity is presented, and an outlook demonstrates how to use the evaluation and objectification of the complexity of a simulation in future systematic optimizations of simulations.
{"title":"Assessing the Complexity of DC-System Simulations","authors":"Jana Ihrens, Tim Schneider, T. A. Kern","doi":"10.1109/COMPENG50184.2022.9905428","DOIUrl":"https://doi.org/10.1109/COMPENG50184.2022.9905428","url":null,"abstract":"Simulations are an important tool in the development of new direct current (DC) grids, as there are hardly any corresponding grids that can be used for testing. For the successful introduction of DC-grid technology, it is necessary to make a decision between risk-taking and system oversizing. Hence, simulations in this new domain have to validly represent reality, while keeping the demands on development time and computation time as low as possible. However, the necessary level of detail is often unclear and so far there is no methodology for balancing complexity and accuracy. Therefore, the initial analysis of complexity is presented, and an outlook demonstrates how to use the evaluation and objectification of the complexity of a simulation in future systematic optimizations of simulations.","PeriodicalId":211056,"journal":{"name":"2022 IEEE Workshop on Complexity in Engineering (COMPENG)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125149859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-18DOI: 10.1109/COMPENG50184.2022.9905470
C. Mesaritakis, G. Sarantoglou, S. Theodoridis, A. Bogris
Neural networks based on reconfigurable photonic integrated chips (RPICs) can offer zero-latency processing, marginal power consumption and operational flexibility. On the other hand, they are subject to, performance affecting, operational/fabrication deviations in their building blocks. Here, we present a Bayesian learning framework that when combined with device characterization, can dramatically decrease power consumption beyond 74% and significantly simplify the driving circuitry.
{"title":"Bayesian Training in Photonic Neural Meshes","authors":"C. Mesaritakis, G. Sarantoglou, S. Theodoridis, A. Bogris","doi":"10.1109/COMPENG50184.2022.9905470","DOIUrl":"https://doi.org/10.1109/COMPENG50184.2022.9905470","url":null,"abstract":"Neural networks based on reconfigurable photonic integrated chips (RPICs) can offer zero-latency processing, marginal power consumption and operational flexibility. On the other hand, they are subject to, performance affecting, operational/fabrication deviations in their building blocks. Here, we present a Bayesian learning framework that when combined with device characterization, can dramatically decrease power consumption beyond 74% and significantly simplify the driving circuitry.","PeriodicalId":211056,"journal":{"name":"2022 IEEE Workshop on Complexity in Engineering (COMPENG)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132428878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-18DOI: 10.1109/COMPENG50184.2022.9905464
D. Davendra, Jason W. Torrence
A novel local search based optimization algorithm named Crosshair Optimizer (CHO) is introduced in this paper. In most algorithms, much of the computational resources are used to explore around a solution space, but in reality, much of the time there are only parts of an optimal solution that can be improved. Using this information, if an algorithm explores the space around an optimal solution using a random number of its dimensions to dictate their placements, rather than all of them, the solution space is explored in a less random fashion. CHO employs a rapid neighbourhood generation on each iteration and selects a sub-sequences of best performing solutions. These selected solutions then randomly generate neighboring solutions only in certain search space dimensions. Exploration is done by randomly generating solutions in only two dimensional axis to the neighbourhood cluster. This speeds up the search process with fine grain sampling, and is quickly able to migrate the search space to another location without using drift migration. Experimentation was conducted on the standard unimodal and multimodal problems, with CHO performing extremely well against standard evolutionary algorithms.
{"title":"Crosshair Optimizer","authors":"D. Davendra, Jason W. Torrence","doi":"10.1109/COMPENG50184.2022.9905464","DOIUrl":"https://doi.org/10.1109/COMPENG50184.2022.9905464","url":null,"abstract":"A novel local search based optimization algorithm named Crosshair Optimizer (CHO) is introduced in this paper. In most algorithms, much of the computational resources are used to explore around a solution space, but in reality, much of the time there are only parts of an optimal solution that can be improved. Using this information, if an algorithm explores the space around an optimal solution using a random number of its dimensions to dictate their placements, rather than all of them, the solution space is explored in a less random fashion. CHO employs a rapid neighbourhood generation on each iteration and selects a sub-sequences of best performing solutions. These selected solutions then randomly generate neighboring solutions only in certain search space dimensions. Exploration is done by randomly generating solutions in only two dimensional axis to the neighbourhood cluster. This speeds up the search process with fine grain sampling, and is quickly able to migrate the search space to another location without using drift migration. Experimentation was conducted on the standard unimodal and multimodal problems, with CHO performing extremely well against standard evolutionary algorithms.","PeriodicalId":211056,"journal":{"name":"2022 IEEE Workshop on Complexity in Engineering (COMPENG)","volume":"267 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134609902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-18DOI: 10.1109/COMPENG50184.2022.9905465
Leonardo Bettini, F. Auteri, F. Dercole
Waves of span-wise velocity at the surface of the flow body, the wall, are known to be very effective in reducing the friction drag in turbulent channels and boundary layers. They can also delay the laminar-turbulent transition. To investigate this interesting property, in this work, we add velocity perturbations within a 3D Blasius boundary layer with wall actuation by means of a standing sinusoidal wave in the stream-wise direction. We look for the initial velocity perturbation pattern able to trigger the maximum energy gain in a given target time. The Navier-Stokes equations act as a constraint in the optimization problem. The results are strongly affected by the actuating parameters, namely the amplitude and wave-length of the sinusoidal profile, in terms of the energy gain and also of the space travelled by initial velocity perturbations during the target time. Opposite behaviours arise, such as an energy gain/loss whenever the actuating wave-length is greater/smaller of the space travelled by the perturbation.
{"title":"Optimal initial perturbations in a boundary layer with wall actuation","authors":"Leonardo Bettini, F. Auteri, F. Dercole","doi":"10.1109/COMPENG50184.2022.9905465","DOIUrl":"https://doi.org/10.1109/COMPENG50184.2022.9905465","url":null,"abstract":"Waves of span-wise velocity at the surface of the flow body, the wall, are known to be very effective in reducing the friction drag in turbulent channels and boundary layers. They can also delay the laminar-turbulent transition. To investigate this interesting property, in this work, we add velocity perturbations within a 3D Blasius boundary layer with wall actuation by means of a standing sinusoidal wave in the stream-wise direction. We look for the initial velocity perturbation pattern able to trigger the maximum energy gain in a given target time. The Navier-Stokes equations act as a constraint in the optimization problem. The results are strongly affected by the actuating parameters, namely the amplitude and wave-length of the sinusoidal profile, in terms of the energy gain and also of the space travelled by initial velocity perturbations during the target time. Opposite behaviours arise, such as an energy gain/loss whenever the actuating wave-length is greater/smaller of the space travelled by the perturbation.","PeriodicalId":211056,"journal":{"name":"2022 IEEE Workshop on Complexity in Engineering (COMPENG)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130765193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-18DOI: 10.1109/COMPENG50184.2022.9905454
V. Ricciardi, L. Manti, M. Lepore, G. Perna, M. Lasalvia, V. Capozzi, I. Delfino
Raman micro-spectroscopy is becoming very popular in the field of radiobiology and radiation oncology for its ability to assess the cellular damage at the molecular level. It can be used to monitor the minimum doses required to lethally damage tumor cells, as well as to reduce the risk of excess dose being delivered to healthy surrounding cells. These results can be achieved also thanks to the development of specific data analysis methods enabling the extraction of information embedded in the Raman spectra of complex samples, such as human cells. Among different data analysis procedures, multivariate analysis has been proven to be particularly effective. The principal component analysis (PCA) method has been largely used for analyzing Raman spectra from cells and tissues. In some cases, the PCA can be performed on selected wavenumber ranges of Raman spectra to get information embedded in those specific ranges (interval-PCA). In the present work, the application of these methods to the analysis of Raman spectra from single SH-SY5Y neuroblastoma cells following the exposure to graded doses of X-rays is reported and specific details from X-ray effects on nucleus and cytoplasm regions are obtained. In addition, the biochemical changes occurring in these cells are also discussed by using an alternative approach, namely the analysis of difference spectra, obtained by subtracting the cytoplasm-related spectrum from the corresponding one detected at the nucleus. It’s worth to note that multivariate analysis has allowed us to unravel the subtle modifications, due to X-ray irradiation, of Raman features related to specific components. These results pave the way to develop proper data analysis methods allowing to manage, on one hand, the complexity of the Raman spectra of cells and tissues and, on the other hand, the high number of spectra needed to consider the intrinsic variability of biological samples.
{"title":"Raman microspectroscopy and multivariate analysis in radiobiology: Study of the effects of X-ray irradiation on neuroblastoma cells","authors":"V. Ricciardi, L. Manti, M. Lepore, G. Perna, M. Lasalvia, V. Capozzi, I. Delfino","doi":"10.1109/COMPENG50184.2022.9905454","DOIUrl":"https://doi.org/10.1109/COMPENG50184.2022.9905454","url":null,"abstract":"Raman micro-spectroscopy is becoming very popular in the field of radiobiology and radiation oncology for its ability to assess the cellular damage at the molecular level. It can be used to monitor the minimum doses required to lethally damage tumor cells, as well as to reduce the risk of excess dose being delivered to healthy surrounding cells. These results can be achieved also thanks to the development of specific data analysis methods enabling the extraction of information embedded in the Raman spectra of complex samples, such as human cells. Among different data analysis procedures, multivariate analysis has been proven to be particularly effective. The principal component analysis (PCA) method has been largely used for analyzing Raman spectra from cells and tissues. In some cases, the PCA can be performed on selected wavenumber ranges of Raman spectra to get information embedded in those specific ranges (interval-PCA). In the present work, the application of these methods to the analysis of Raman spectra from single SH-SY5Y neuroblastoma cells following the exposure to graded doses of X-rays is reported and specific details from X-ray effects on nucleus and cytoplasm regions are obtained. In addition, the biochemical changes occurring in these cells are also discussed by using an alternative approach, namely the analysis of difference spectra, obtained by subtracting the cytoplasm-related spectrum from the corresponding one detected at the nucleus. It’s worth to note that multivariate analysis has allowed us to unravel the subtle modifications, due to X-ray irradiation, of Raman features related to specific components. These results pave the way to develop proper data analysis methods allowing to manage, on one hand, the complexity of the Raman spectra of cells and tissues and, on the other hand, the high number of spectra needed to consider the intrinsic variability of biological samples.","PeriodicalId":211056,"journal":{"name":"2022 IEEE Workshop on Complexity in Engineering (COMPENG)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125923314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-18DOI: 10.1109/COMPENG50184.2022.9905435
Michal Pluhacek, T. Kadavy, Anezka Kazikova, Adam Viktorin, R. Šenkeřík
In this paper, we present the relation between the inner dynamics of the particle swarm optimization algorithm and the properties of a complex network recording the information transfer in the population. Using population diversity as an example, we argue that the complex network analysis is a viable tool for assessing the state of the population and the eventual necessity of an adaptive intervention.
{"title":"Inner Dynamics of Particle Swarm Optimization Interpreted by Complex Network Analysis","authors":"Michal Pluhacek, T. Kadavy, Anezka Kazikova, Adam Viktorin, R. Šenkeřík","doi":"10.1109/COMPENG50184.2022.9905435","DOIUrl":"https://doi.org/10.1109/COMPENG50184.2022.9905435","url":null,"abstract":"In this paper, we present the relation between the inner dynamics of the particle swarm optimization algorithm and the properties of a complex network recording the information transfer in the population. Using population diversity as an example, we argue that the complex network analysis is a viable tool for assessing the state of the population and the eventual necessity of an adaptive intervention.","PeriodicalId":211056,"journal":{"name":"2022 IEEE Workshop on Complexity in Engineering (COMPENG)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114858438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-18DOI: 10.1109/COMPENG50184.2022.9905439
I. Diop, C. Cherifi, C. Diallo, H. Cherifi
The air transportation network is a critical infrastructure in our connected world. Therefore, understanding its robustness to targeted attacks is essential. Extensive research has investigated how removing a particular class of nodes impacts connectivity, efficiency, and security. However, the impact of its mesoscopic structuration remains largely unexplored. To fill this gap, we investigate how targeted attacks on the global weighted air transport network impact its components in this study. Indeed, the weighted world air transportation network includes five local components covering different regions (North America-Caribbean, Europe-Russia, East and Southeast Asia-Oceania, Africa-Middle East-South Asia, South America) and a global component scattered around the world. We study and compare two prevalent attacks (weighted Closeness and weighted Eigenvector). The results show that as the percentage of airports removed increases, the local components progressively separate from the global air transportation network. One needs to remove a lower fraction of top Weighted Closeness airports to isolate regions compared to the Weighted Eigenvector attack. Furthermore, traveling in areas separated by the Weighted Closeness attack is still quite effective. In contrast, the Weighted Eigenvector attack is more damaging for regional transportation. This study opens new perspectives for better understanding the global air transportation network resilience.
{"title":"Robustness of the Weighted World Air Transportation Network Components","authors":"I. Diop, C. Cherifi, C. Diallo, H. Cherifi","doi":"10.1109/COMPENG50184.2022.9905439","DOIUrl":"https://doi.org/10.1109/COMPENG50184.2022.9905439","url":null,"abstract":"The air transportation network is a critical infrastructure in our connected world. Therefore, understanding its robustness to targeted attacks is essential. Extensive research has investigated how removing a particular class of nodes impacts connectivity, efficiency, and security. However, the impact of its mesoscopic structuration remains largely unexplored. To fill this gap, we investigate how targeted attacks on the global weighted air transport network impact its components in this study. Indeed, the weighted world air transportation network includes five local components covering different regions (North America-Caribbean, Europe-Russia, East and Southeast Asia-Oceania, Africa-Middle East-South Asia, South America) and a global component scattered around the world. We study and compare two prevalent attacks (weighted Closeness and weighted Eigenvector). The results show that as the percentage of airports removed increases, the local components progressively separate from the global air transportation network. One needs to remove a lower fraction of top Weighted Closeness airports to isolate regions compared to the Weighted Eigenvector attack. Furthermore, traveling in areas separated by the Weighted Closeness attack is still quite effective. In contrast, the Weighted Eigenvector attack is more damaging for regional transportation. This study opens new perspectives for better understanding the global air transportation network resilience.","PeriodicalId":211056,"journal":{"name":"2022 IEEE Workshop on Complexity in Engineering (COMPENG)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115687282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-18DOI: 10.1109/COMPENG50184.2022.9905468
S. Čelikovský, M. Anderle
The almost linear form that is state and feedback equivalent to the dynamics of the so-called three-link (aka biped with torso) is derived and proved here. This result is then applied to the walking design with downward torso movement imitating balancing role of a hand. This motivates a challenging idea: the balancing role of hands in two-dimensional walking consists in synchronizing the hand angle with the hip angle in such a way that the resulting restricted dynamics is exact feedback linearizable. Results are demonstrated by the simulations of a single step including walking animations.
{"title":"On the equivalence of the three-link to the almost linear form*","authors":"S. Čelikovský, M. Anderle","doi":"10.1109/COMPENG50184.2022.9905468","DOIUrl":"https://doi.org/10.1109/COMPENG50184.2022.9905468","url":null,"abstract":"The almost linear form that is state and feedback equivalent to the dynamics of the so-called three-link (aka biped with torso) is derived and proved here. This result is then applied to the walking design with downward torso movement imitating balancing role of a hand. This motivates a challenging idea: the balancing role of hands in two-dimensional walking consists in synchronizing the hand angle with the hip angle in such a way that the resulting restricted dynamics is exact feedback linearizable. Results are demonstrated by the simulations of a single step including walking animations.","PeriodicalId":211056,"journal":{"name":"2022 IEEE Workshop on Complexity in Engineering (COMPENG)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122905581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-18DOI: 10.1109/COMPENG50184.2022.9905463
K. Tamersit, A. Boualleg, H. Bourouba
In this paper, a new gas microsensor based on graphene field-effect transistor (GFET) is proposed, modeled, and studied through a compact drain current model. This latter is based on drift-diffusion carrier transport, which takes into account the sensing and transduction mechanisms and includes the dimensional and physical sensor parameters. The used sensing principle is based on the work function modulation technique. The shift in Dirac point voltage is considered as a sensing metric. The proposed GFET-based gas microsensor, that employs a top sensitive gate as reference and a back gate for control, has exhibited an ultra-sensitive performance toward the toxic gases. The obtained results make the suggested GFETbased gas microsensor as a promising candidate for highperformance and low-cost monitoring and defense applications.
{"title":"High-Performance Detection of Toxic Gases Using a New Microsensor based on Graphene Field-Effect Transistor","authors":"K. Tamersit, A. Boualleg, H. Bourouba","doi":"10.1109/COMPENG50184.2022.9905463","DOIUrl":"https://doi.org/10.1109/COMPENG50184.2022.9905463","url":null,"abstract":"In this paper, a new gas microsensor based on graphene field-effect transistor (GFET) is proposed, modeled, and studied through a compact drain current model. This latter is based on drift-diffusion carrier transport, which takes into account the sensing and transduction mechanisms and includes the dimensional and physical sensor parameters. The used sensing principle is based on the work function modulation technique. The shift in Dirac point voltage is considered as a sensing metric. The proposed GFET-based gas microsensor, that employs a top sensitive gate as reference and a back gate for control, has exhibited an ultra-sensitive performance toward the toxic gases. The obtained results make the suggested GFETbased gas microsensor as a promising candidate for highperformance and low-cost monitoring and defense applications.","PeriodicalId":211056,"journal":{"name":"2022 IEEE Workshop on Complexity in Engineering (COMPENG)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130247181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-18DOI: 10.1109/COMPENG50184.2022.9905440
T. Kadavy, Michal Pluhacek, Adam Viktorin, Anezka Kazikova, R. Šenkeřík
During the developing phase of the new evolutionary algorithm (EA) or the analysis, several techniques or measurements are used to capture the inner dynamic of an algorithm. Besides the usual ones, for example, convergence graphs, population diversity, or complex networks, the scientists may also use clustering. Clustering analysis may naturally be used to analyze the grouping of individuals in swarm-based algorithms. This paper examines the possibilities of the clustering analysis for the Self-Organizing Migrating Algorithm with CLustering-aided migration (SOMA-CL). The algorithm is described in detail, together with several cluster analyses which can be used to investigate the behavior of the algorithm.
{"title":"Exploring clustering in SOMA","authors":"T. Kadavy, Michal Pluhacek, Adam Viktorin, Anezka Kazikova, R. Šenkeřík","doi":"10.1109/COMPENG50184.2022.9905440","DOIUrl":"https://doi.org/10.1109/COMPENG50184.2022.9905440","url":null,"abstract":"During the developing phase of the new evolutionary algorithm (EA) or the analysis, several techniques or measurements are used to capture the inner dynamic of an algorithm. Besides the usual ones, for example, convergence graphs, population diversity, or complex networks, the scientists may also use clustering. Clustering analysis may naturally be used to analyze the grouping of individuals in swarm-based algorithms. This paper examines the possibilities of the clustering analysis for the Self-Organizing Migrating Algorithm with CLustering-aided migration (SOMA-CL). The algorithm is described in detail, together with several cluster analyses which can be used to investigate the behavior of the algorithm.","PeriodicalId":211056,"journal":{"name":"2022 IEEE Workshop on Complexity in Engineering (COMPENG)","volume":"143 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122049667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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