Damage identification of the offshore floating wind turbine by vibration/dynamic signals is one of the important and new research fields in the Structural Health Monitoring（SHM）. In this paper a new damage identific...Damage identification of the offshore floating wind turbine by vibration/dynamic signals is one of the important and new research fields in the Structural Health Monitoring（SHM）. In this paper a new damage identification method is proposed based on meta-heuristic algorithms using the dynamic response of the TLP（Tension-Leg Platform） floating wind turbine structure. The Genetic Algorithms（GA）, Artificial Immune System（AIS）, Particle Swarm Optimization（PSO）, and Artificial Bee Colony（ABC） are chosen for minimizing the object function, defined properly for damage identification purpose. In addition to studying the capability of mentioned algorithms in correctly identifying the damage, the effect of the response type on the results of identification is studied. Also, the results of proposed damage identification are investigated with considering possible uncertainties of the structure. Finally, for evaluating the proposed method in real condition, a 1/100 scaled experimental setup of TLP Floating Wind Turbine（TLPFWT） is provided in a laboratory scale and the proposed damage identification method is applied to the scaled turbine.展开更多
In this study, Imperialistic Competitive Algorithm（ICA） is utilized for locating the critical failure surface and computing the factor of safety（FOS） in a slope stability analysis based on the limit equilibrium ap...In this study, Imperialistic Competitive Algorithm（ICA） is utilized for locating the critical failure surface and computing the factor of safety（FOS） in a slope stability analysis based on the limit equilibrium approach. The factor of safety relating to each trial slip surface is calculated using a simplified algorithm of the Morgenstern-Price method, which satisfies both the force and the moment equilibriums. General slip surface is considered non-circular in this study that is constituted by linking random straight lines.To explore the performance of the proposed algorithm, four benchmark test problems are analyzed. The results demonstrate that the present techniques can provide reliable, accurate and efficient solutions for locating the critical failure surface and relating FOS. Moreover, in contrast with previous studies the present algorithm could reach the lower value of FOS and reached more exact solutions.展开更多
The meta search engines provide service to the users by dispensing the users' requests to the existing search engines. The existing search engines selected by meta search engine determine the searching quality. Be...The meta search engines provide service to the users by dispensing the users' requests to the existing search engines. The existing search engines selected by meta search engine determine the searching quality. Because the performance of the existing search engines and the users' requests are changed dynamically, it is not favorable for the fixed search engines to optimize the holistic performance of the meta search engine. This paper applies the genetic algorithm (GA) to realize the scheduling strategy of agent manager in our meta search engine, GSE(general search engine), which can simulate the evolution process of living things more lively and more efficiently. By using GA, the combination of search engines can be optimized and hence the holistic performance of GSE can be improved dramatically.展开更多
In disaster relief operations,multiple UAVs can be used to search for trapped people.In recent years,many researchers have proposed machine le arning-based algorithms,sampling-based algorithms,and heuristic algorithms...In disaster relief operations,multiple UAVs can be used to search for trapped people.In recent years,many researchers have proposed machine le arning-based algorithms,sampling-based algorithms,and heuristic algorithms to solve the problem of multi-UAV path planning.The Dung Beetle Optimization(DBO)algorithm has been widely applied due to its diverse search patterns in the above algorithms.However,the update strategies for the rolling and thieving dung beetles of the DBO algorithm are overly simplistic,potentially leading to an inability to fully explore the search space and a tendency to converge to local optima,thereby not guaranteeing the discovery of the optimal path.To address these issues,we propose an improved DBO algorithm guided by the Landmark Operator(LODBO).Specifically,we first use tent mapping to update the population strategy,which enables the algorithm to generate initial solutions with enhanced diversity within the search space.Second,we expand the search range of the rolling ball dung beetle by using the landmark factor.Finally,by using the adaptive factor that changes with the number of iterations.,we improve the global search ability of the stealing dung beetle,making it more likely to escape from local optima.To verify the effectiveness of the proposed method,extensive simulation experiments are conducted,and the result shows that the LODBO algorithm can obtain the optimal path using the shortest time compared with the Genetic Algorithm(GA),the Gray Wolf Optimizer(GWO),the Whale Optimization Algorithm(WOA)and the original DBO algorithm in the disaster search and rescue task set.展开更多
In this paper,we propose a Rough Set assisted Meta-Learning method on how to select the most-suited machine-learning algorithms with minimal effort for a new given dataset. A k-Nearest Neighbor (k-NN) algorithm is use...In this paper,we propose a Rough Set assisted Meta-Learning method on how to select the most-suited machine-learning algorithms with minimal effort for a new given dataset. A k-Nearest Neighbor (k-NN) algorithm is used to recognize the most similar datasets that have been performed by all of the candidate algorithms.By matching the most similar datasets we found,the corresponding performance of the candidate algorithms is used to generate recommendation to the user.The performance derives from a multi-criteria evaluation measure-ARR,which contains both accuracy and time.Furthermore,after applying Rough Set theory,we can find the redundant properties of the dataset.Thus,we can speed up the ranking process and increase the accuracy by using the reduct of the meta attributes.展开更多
This paper introduces Soccer League Competition (SLC) algorithm as a new optimization technique for solving nonlinear systems of equations. Fundamental ideas of the method are inspired from soccer leagues and based on...This paper introduces Soccer League Competition (SLC) algorithm as a new optimization technique for solving nonlinear systems of equations. Fundamental ideas of the method are inspired from soccer leagues and based on the competitions among teams and players. Like other meta-heuristic methods, the proposed technique starts with an initial population. Population individuals called players are in two types: fixed players and substitutes that all together form some teams. The competition among teams to take the possession of the top ranked positions in the league table and the internal competitions between players in each team for personal improvements results in the convergence of population individuals to the global optimum. Results of applying the proposed algorithm in solving nonlinear systems of equations demonstrate that SLC converges to the answer more accurately and rapidly in comparison with other Meta-heuristic and Newton-type methods.展开更多
BACKGROUND: Although the Australasian Triage Scale(ATS) has been developed two decades ago, its reliability has not been def ined; therefore, we present a meta-analyis of the reliability of the ATS in order to reveal ...BACKGROUND: Although the Australasian Triage Scale(ATS) has been developed two decades ago, its reliability has not been def ined; therefore, we present a meta-analyis of the reliability of the ATS in order to reveal to what extent the ATS is reliable.DATA SOURCES: Electronic databases were searched to March 2014. The included studies were those that reported samples size, reliability coefficients, and adequate description of the ATS reliability assessment. The guidelines for reporting reliability and agreement studies(GRRAS) were used. Two reviewers independently examined abstracts and extracted data. The effect size was obtained by the z-transformation of reliability coefficients. Data were pooled with random-effects models, and meta-regression was done based on the method of moment's estimator.RESULTS: Six studies were included in this study at last. Pooled coefficient for the ATS was substantial 0.428(95%CI 0.340–0.509). The rate of mis-triage was less than fifty percent. The agreement upon the adult version is higher than the pediatric version.CONCLUSION: The ATS has shown an acceptable level of overall reliability in the emergency department, but it needs more development to reach an almost perfect agreement.展开更多
Background：Many meta-analyses investigating gum chewing for postoperative recovery after colorectal surgery have been published with inconsistent findings.Therefore,we performed this study to systematically review th...Background：Many meta-analyses investigating gum chewing for postoperative recovery after colorectal surgery have been published with inconsistent findings.Therefore,we performed this study to systematically review these overlapping meta-analyses and offer clinical recommendations based on the current best evidence for decision makers.Methods：Multiple databases,including PubMed,EMBASE,Cochrane Library,Chinese BioMedical Literature on disc（CBMdisc）,China National Knowledge Infrastructure（CNKI）,Chinese Wanfang and Chinese VIP,were searched through October 2016.We included meta-analyses investigating the effectiveness of chewing gum for postoperative ileus after colorectal resection.Two investigators independently scanned and evaluated eligible meta-analyses,extracted essential information,assessed the methodological quality with the Assessment of Multiple Systematic Reviews（AMSTAR） tool and Oxford Levels of Evidence,and used the Jadad decision algorithm at each step for all procedures.Heterogeneity ≤50%was accepted.Results：Ten meta-analyses were included in our study.The AMSTAR scores varied from 5 to 9,with a median of 7.7.Most heterogeneity fell into the acceptable range.After implementing the Jadad decision algorithm,two meta-analyses of RCTs were selected based on search strategies and the implications of selection.The available best evidence indicated that gum chewing significantly reduced time to first flatus,time to first bowel movement,time to first bowel sounds and length of hospital stay.However,these two meta-analyses reached inconsistent conclusions as to the complications and economic benefits.Conclusions：With the current best available evidence,we suggest gum chewing is beneficial for gastrointestinal function and reducing postoperative ileus.展开更多
Electromagnetism-like (EML) algorithm is a new evolutionary algorithm that bases on the electromagnetic attraction and repulsion among particles. It was originally proposed to solve optimization problems with bounded ...Electromagnetism-like (EML) algorithm is a new evolutionary algorithm that bases on the electromagnetic attraction and repulsion among particles. It was originally proposed to solve optimization problems with bounded variables. Since its inception, many variants of the EML algorithm have been proposed in the literature. However, it remains unclear how to simulate the electromagnetic heuristics in an EML algorithm effectively to achieve the best performance. This study surveys and compares the EML algorithms in the literature. Furthermore, local search and perturbed point are two techniques commonly used in an EML algorithm to fine tune the solution and to help escaping from local optimums, respectively. Performance study is conducted to understand their impact on an EML algorithm.展开更多
文摘Damage identification of the offshore floating wind turbine by vibration/dynamic signals is one of the important and new research fields in the Structural Health Monitoring（SHM）. In this paper a new damage identification method is proposed based on meta-heuristic algorithms using the dynamic response of the TLP（Tension-Leg Platform） floating wind turbine structure. The Genetic Algorithms（GA）, Artificial Immune System（AIS）, Particle Swarm Optimization（PSO）, and Artificial Bee Colony（ABC） are chosen for minimizing the object function, defined properly for damage identification purpose. In addition to studying the capability of mentioned algorithms in correctly identifying the damage, the effect of the response type on the results of identification is studied. Also, the results of proposed damage identification are investigated with considering possible uncertainties of the structure. Finally, for evaluating the proposed method in real condition, a 1/100 scaled experimental setup of TLP Floating Wind Turbine（TLPFWT） is provided in a laboratory scale and the proposed damage identification method is applied to the scaled turbine.
文摘In this study, Imperialistic Competitive Algorithm（ICA） is utilized for locating the critical failure surface and computing the factor of safety（FOS） in a slope stability analysis based on the limit equilibrium approach. The factor of safety relating to each trial slip surface is calculated using a simplified algorithm of the Morgenstern-Price method, which satisfies both the force and the moment equilibriums. General slip surface is considered non-circular in this study that is constituted by linking random straight lines.To explore the performance of the proposed algorithm, four benchmark test problems are analyzed. The results demonstrate that the present techniques can provide reliable, accurate and efficient solutions for locating the critical failure surface and relating FOS. Moreover, in contrast with previous studies the present algorithm could reach the lower value of FOS and reached more exact solutions.
基金Supported in part by the National Natural Science F oundation of China(NSFC) (6 0 0 730 12 )
文摘The meta search engines provide service to the users by dispensing the users' requests to the existing search engines. The existing search engines selected by meta search engine determine the searching quality. Because the performance of the existing search engines and the users' requests are changed dynamically, it is not favorable for the fixed search engines to optimize the holistic performance of the meta search engine. This paper applies the genetic algorithm (GA) to realize the scheduling strategy of agent manager in our meta search engine, GSE(general search engine), which can simulate the evolution process of living things more lively and more efficiently. By using GA, the combination of search engines can be optimized and hence the holistic performance of GSE can be improved dramatically.
基金supported by the National Natural Science Foundation of China(No.62373027).
文摘In disaster relief operations,multiple UAVs can be used to search for trapped people.In recent years,many researchers have proposed machine le arning-based algorithms,sampling-based algorithms,and heuristic algorithms to solve the problem of multi-UAV path planning.The Dung Beetle Optimization(DBO)algorithm has been widely applied due to its diverse search patterns in the above algorithms.However,the update strategies for the rolling and thieving dung beetles of the DBO algorithm are overly simplistic,potentially leading to an inability to fully explore the search space and a tendency to converge to local optima,thereby not guaranteeing the discovery of the optimal path.To address these issues,we propose an improved DBO algorithm guided by the Landmark Operator(LODBO).Specifically,we first use tent mapping to update the population strategy,which enables the algorithm to generate initial solutions with enhanced diversity within the search space.Second,we expand the search range of the rolling ball dung beetle by using the landmark factor.Finally,by using the adaptive factor that changes with the number of iterations.,we improve the global search ability of the stealing dung beetle,making it more likely to escape from local optima.To verify the effectiveness of the proposed method,extensive simulation experiments are conducted,and the result shows that the LODBO algorithm can obtain the optimal path using the shortest time compared with the Genetic Algorithm(GA),the Gray Wolf Optimizer(GWO),the Whale Optimization Algorithm(WOA)and the original DBO algorithm in the disaster search and rescue task set.
文摘In this paper,we propose a Rough Set assisted Meta-Learning method on how to select the most-suited machine-learning algorithms with minimal effort for a new given dataset. A k-Nearest Neighbor (k-NN) algorithm is used to recognize the most similar datasets that have been performed by all of the candidate algorithms.By matching the most similar datasets we found,the corresponding performance of the candidate algorithms is used to generate recommendation to the user.The performance derives from a multi-criteria evaluation measure-ARR,which contains both accuracy and time.Furthermore,after applying Rough Set theory,we can find the redundant properties of the dataset.Thus,we can speed up the ranking process and increase the accuracy by using the reduct of the meta attributes.
文摘This paper introduces Soccer League Competition (SLC) algorithm as a new optimization technique for solving nonlinear systems of equations. Fundamental ideas of the method are inspired from soccer leagues and based on the competitions among teams and players. Like other meta-heuristic methods, the proposed technique starts with an initial population. Population individuals called players are in two types: fixed players and substitutes that all together form some teams. The competition among teams to take the possession of the top ranked positions in the league table and the internal competitions between players in each team for personal improvements results in the convergence of population individuals to the global optimum. Results of applying the proposed algorithm in solving nonlinear systems of equations demonstrate that SLC converges to the answer more accurately and rapidly in comparison with other Meta-heuristic and Newton-type methods.
文摘BACKGROUND: Although the Australasian Triage Scale(ATS) has been developed two decades ago, its reliability has not been def ined; therefore, we present a meta-analyis of the reliability of the ATS in order to reveal to what extent the ATS is reliable.DATA SOURCES: Electronic databases were searched to March 2014. The included studies were those that reported samples size, reliability coefficients, and adequate description of the ATS reliability assessment. The guidelines for reporting reliability and agreement studies(GRRAS) were used. Two reviewers independently examined abstracts and extracted data. The effect size was obtained by the z-transformation of reliability coefficients. Data were pooled with random-effects models, and meta-regression was done based on the method of moment's estimator.RESULTS: Six studies were included in this study at last. Pooled coefficient for the ATS was substantial 0.428(95%CI 0.340–0.509). The rate of mis-triage was less than fifty percent. The agreement upon the adult version is higher than the pediatric version.CONCLUSION: The ATS has shown an acceptable level of overall reliability in the emergency department, but it needs more development to reach an almost perfect agreement.
文摘Background：Many meta-analyses investigating gum chewing for postoperative recovery after colorectal surgery have been published with inconsistent findings.Therefore,we performed this study to systematically review these overlapping meta-analyses and offer clinical recommendations based on the current best evidence for decision makers.Methods：Multiple databases,including PubMed,EMBASE,Cochrane Library,Chinese BioMedical Literature on disc（CBMdisc）,China National Knowledge Infrastructure（CNKI）,Chinese Wanfang and Chinese VIP,were searched through October 2016.We included meta-analyses investigating the effectiveness of chewing gum for postoperative ileus after colorectal resection.Two investigators independently scanned and evaluated eligible meta-analyses,extracted essential information,assessed the methodological quality with the Assessment of Multiple Systematic Reviews（AMSTAR） tool and Oxford Levels of Evidence,and used the Jadad decision algorithm at each step for all procedures.Heterogeneity ≤50%was accepted.Results：Ten meta-analyses were included in our study.The AMSTAR scores varied from 5 to 9,with a median of 7.7.Most heterogeneity fell into the acceptable range.After implementing the Jadad decision algorithm,two meta-analyses of RCTs were selected based on search strategies and the implications of selection.The available best evidence indicated that gum chewing significantly reduced time to first flatus,time to first bowel movement,time to first bowel sounds and length of hospital stay.However,these two meta-analyses reached inconsistent conclusions as to the complications and economic benefits.Conclusions：With the current best available evidence,we suggest gum chewing is beneficial for gastrointestinal function and reducing postoperative ileus.
文摘Electromagnetism-like (EML) algorithm is a new evolutionary algorithm that bases on the electromagnetic attraction and repulsion among particles. It was originally proposed to solve optimization problems with bounded variables. Since its inception, many variants of the EML algorithm have been proposed in the literature. However, it remains unclear how to simulate the electromagnetic heuristics in an EML algorithm effectively to achieve the best performance. This study surveys and compares the EML algorithms in the literature. Furthermore, local search and perturbed point are two techniques commonly used in an EML algorithm to fine tune the solution and to help escaping from local optimums, respectively. Performance study is conducted to understand their impact on an EML algorithm.
