Stereoscopic agriculture,as an advanced method of agricultural production,poses new challenges for multi-task trajectory planning of unmanned aerial vehicles(UAVs).To address the need for UAVs to perform multi-task tr...Stereoscopic agriculture,as an advanced method of agricultural production,poses new challenges for multi-task trajectory planning of unmanned aerial vehicles(UAVs).To address the need for UAVs to perform multi-task trajectory planning in stereoscopic agriculture,a multi-task trajectory planning model and algorithm(IEP-AO)that synthesizes flight safety and flight efficiency is proposed.Based on the requirements of stereoscopic agricultural geomorphological features and operational characteristics,the multi-task trajectory planning model is ensured by constructing targeted constraints at five aspects,including the path,slope,altitude,corner,energy and obstacle threat,to improve the effectiveness of the trajectory planning model.And combined with the path optimization algorithm,an Aquila optimizer(IEP-AO)based on the interference-enhanced combination model is proposed,which can help UAVs to improve the trajectory search capability in complex operation space and large-scale operation tasks,and jump out of the locally optimal trajectory path region timely,to generate the optimal trajectory planning plan that can adapt to the diversity of the tasks and the flight efficiency.Meanwhile,four simulated flights with different operation scales and different scene constraints were conducted under the constructed real 3Dimension scene,and the experimental results can show that the proposedmulti-task trajectory planning method canmeet themulti-task requirements in stereoscopic agriculture and improve the mission execution efficiency and agricultural production effect of UAV.展开更多
Aquila Optimizer(AO)is a recently proposed population-based optimization technique inspired by Aquila’s behavior in catching prey.AO is applied in various applications and its numerous variants were proposed in the l...Aquila Optimizer(AO)is a recently proposed population-based optimization technique inspired by Aquila’s behavior in catching prey.AO is applied in various applications and its numerous variants were proposed in the literature.However,chaos theory has not been extensively investigated in AO.Moreover,it is still not applied in the parameter estimation of electro-hydraulic systems.In this work,ten well-defined chaotic maps were integrated into a narrowed exploitation of AO for the development of a robust chaotic optimization technique.An extensive investigation of twenty-three mathematical benchmarks and ten IEEE Congress on Evolutionary Computation(CEC)functions shows that chaotic Aquila optimization techniques perform better than the baseline technique.The investigation is further conducted on parameter estimation of an electro-hydraulic control system,which is performed on various noise levels and shows that the proposed chaotic AO with Piecewise map(CAO6)achieves the best fitness values of and at noise levels and respectively.Friedman test 2.873E-05,1.014E-04,8.728E-031.300E-03,1.300E-02,1.300E-01,for repeated measures,computational analysis,and Taguchi test reflect the superiority of CAO6 against the state of the arts,demonstrating its potential for addressing various engineering optimization problems.However,the sensitivity to parameter tuning may limit its direct application to complex optimization scenarios.展开更多
This research study aims to enhance the optimization performance of a newly emerged Aquila Optimization algorithm by incorporating chaotic sequences rather than using uniformly generated Gaussian random numbers.This w...This research study aims to enhance the optimization performance of a newly emerged Aquila Optimization algorithm by incorporating chaotic sequences rather than using uniformly generated Gaussian random numbers.This work employs 25 different chaotic maps under the framework of Aquila Optimizer.It considers the ten best chaotic variants for performance evaluation on multidimensional test functions composed of unimodal and multimodal problems,which have yet to be studied in past literature works.It was found that Ikeda chaotic map enhanced Aquila Optimization algorithm yields the best predictions and becomes the leading method in most of the cases.To test the effectivity of this chaotic variant on real-world optimization problems,it is employed on two constrained engineering design problems,and its effectiveness has been verified.Finally,phase equilibrium and semi-empirical parameter estimation problems have been solved by the proposed method,and respective solutions have been compared with those obtained from state-of-art optimizers.It is observed that CH01 can successfully cope with the restrictive nonlinearities and nonconvexities of parameter estimation and phase equilibrium problems,showing the capabilities of yielding minimum prediction error values of no more than 0.05 compared to the remaining algorithms utilized in the performance benchmarking process.展开更多
A Mw6.4 earthquake occurred in L＇Aquila, central Italy at 1：32：42 （UTC）, April 6, 2009. We quickly obtained the moment tensor solution of the earthquake by inverting the P waveforms of broadband recordings from t...A Mw6.4 earthquake occurred in L＇Aquila, central Italy at 1：32：42 （UTC）, April 6, 2009. We quickly obtained the moment tensor solution of the earthquake by inverting the P waveforms of broadband recordings from the global seismographic network （GSN） stations using the quick technique of moment tensor inversion, and further inferred that the nodal plane of strike 132°, dip 53° and rake -103° is the seismogenic fault.展开更多
Oil production estimation plays a critical role in economic plans for local governments and organizations.Therefore,many studies applied different Artificial Intelligence(AI)based meth-ods to estimate oil production i...Oil production estimation plays a critical role in economic plans for local governments and organizations.Therefore,many studies applied different Artificial Intelligence(AI)based meth-ods to estimate oil production in different countries.The Adaptive Neuro-Fuzzy Inference System(ANFIS)is a well-known model that has been successfully employed in various applica-tions,including time-series forecasting.However,the ANFIS model faces critical shortcomings in its parameters during the configuration process.From this point,this paper works to solve the drawbacks of the ANFIS by optimizing ANFIS parameters using a modified Aquila Optimizer(AO)with the Opposition-Based Learning(OBL)technique.The main idea of the developed model,AOOBL-ANFIS,is to enhance the search process of the AO and use the AOOBL to boost the performance of the ANFIS.The proposed model is evaluated using real-world oil produc-tion datasets collected from different oilfields using several performance metrics,including Root Mean Square Error(RMSE),Mean Absolute Error(MAE),coefficient of determination(R2),Standard Deviation(Std),and computational time.Moreover,the AOOBL-ANFIS model is compared to several modified ANFIS models include Particle Swarm Optimization(PSO)-ANFIS,Grey Wolf Optimizer(GWO)-ANFIS,Sine Cosine Algorithm(SCA)-ANFIS,Slime Mold Algorithm(SMA)-ANFIS,and Genetic Algorithm(GA)-ANFIS,respectively.Additionally,it is compared to well-known time series forecasting methods,namely,Autoregressive Integrated Moving Average(ARIMA),Long Short-Term Memory(LSTM),Seasonal Autoregressive Integrated Moving Average(SARIMA),and Neural Network(NN).The outcomes verified the high performance of the AOOBL-ANFIS,which outperformed the classic ANFIS model and the compared models.展开更多
To better understand the mechanism of the Mw6.3 L＇Aquila （Central Italy） earthquake occurred in 2009, global positioning system （GPS） and interferometric synthetic aperture radar （InSAR） data were used to deriv...To better understand the mechanism of the Mw6.3 L＇Aquila （Central Italy） earthquake occurred in 2009, global positioning system （GPS） and interferometric synthetic aperture radar （InSAR） data were used to derive the coseismic slip distribution of the earthquake fault. Firstly, based on the homogeneous elastic half-space model, the fault geometric parameters were solved by the genetic algorithm. The best fitting model shows that the fault is a 13.7 km×14.1 km rectangular fault, in 139.3° strike direction and 50.2° southwest-dipping. Secondly, fixing the optimal fault geometric parameters, the fault plane was extended and discretized into 16× 16 patches, each with a size of 1 kmx 1 krn, and the non-uniform slip distribution of the fault was inverted by the steepest descent method with an appropriate smoothing ratio based on the layered crustal structure model. The preferred solution shows that the fault is mainly a normal fault with slight right-lateral strike slip, the maximum slip of 1.01 m is located in the depth of 8.28 km, the average rake is -100.9°, and the total geodetic moment is about 3.34× 1018 N.m （Mw 6.28）. The results are much closer than previous studies in comparison with the seismological estimation. These demonstrate that the coseismic fault slip distribution of the L＇Aauila earthauake inverted by the crustal model considering layered characters is reliable.展开更多
In this work,we propose a real proportional-integral-derivative plus second-order derivative(PIDD2)controller as an efficient controller for vehicle cruise control systems to address the challenging issues related to ...In this work,we propose a real proportional-integral-derivative plus second-order derivative(PIDD2)controller as an efficient controller for vehicle cruise control systems to address the challenging issues related to efficient operation.In this regard,this paper is the first report in the literature demonstrating the implementation of a real PIDD2 controller for controlling the respective system.We construct a novel and efficient metaheuristic algorithm by improving the performance of the Aquila Optimizer via chaotic local search and modified opposition-based learning strategies and use it as an excellently performing tuning mechanism.We also propose a simple yet effective objective function to increase the performance of the proposed algorithm(CmOBL-AO)to adjust the real PIDD2 controller's parameters effectively.We show the CmOBL-AO algorithm to perform better than the differential evolution algorithm,gravitational search algorithm,African vultures optimization,and the Aquila Optimizer using well-known unimodal,multimodal benchmark functions.CEC2019 test suite is also used to perform ablation experiments to reveal the separate contributions of chaotic local search and modified opposition-based learning strategies to the CmOBL-AO algorithm.For the vehicle cruise control system,we confirm the more excellent performance of the proposed method against particle swarm,gray wolf,salp swarm,and original Aquila optimizers using statistical,Wilcoxon signed-rank,time response,robustness,and disturbance rejection analyses.We also use fourteen reported methods in the literature for the vehicle cruise control system to further verify the more promising performance of the CmOBL-AO-based real PIDD2 controller from a wider perspective.The excellent performance of the proposed method is also illustrated through different quality indicators and different operating speeds.Lastly,we also demonstrate the good performing capability of the CmOBL-AO algorithm for real traffic cases.We show the CmOBL-AO-based real PIDD2 controller as the most efficient method to control a vehicle cruise control system.展开更多
Cyber-physical system(CPS)is a concept that integrates every computer-driven system interacting closely with its physical environment.Internet-of-things(IoT)is a union of devices and technologies that provide universa...Cyber-physical system(CPS)is a concept that integrates every computer-driven system interacting closely with its physical environment.Internet-of-things(IoT)is a union of devices and technologies that provide universal interconnection mechanisms between the physical and digital worlds.Since the complexity level of the CPS increases,an adversary attack becomes possible in several ways.Assuring security is a vital aspect of the CPS environment.Due to the massive surge in the data size,the design of anomaly detection techniques becomes a challenging issue,and domain-specific knowledge can be applied to resolve it.This article develops an Aquila Optimizer with Parameter Tuned Machine Learning Based Anomaly Detection(AOPTML-AD)technique in the CPS environment.The presented AOPTML-AD model intends to recognize and detect abnormal behaviour in the CPS environment.The presented AOPTML-AD framework initially pre-processes the network data by converting them into a compatible format.Besides,the improved Aquila optimization algorithm-based feature selection(IAOA-FS)algorithm is designed to choose an optimal feature subset.Along with that,the chimp optimization algorithm(ChOA)with an adaptive neuro-fuzzy inference system(ANFIS)model can be employed to recognise anomalies in the CPS environment.The ChOA is applied for optimal adjusting of the membership function(MF)indulged in the ANFIS method.The performance validation of the AOPTML-AD algorithm is carried out using the benchmark dataset.The extensive comparative study reported the better performance of the AOPTML-AD technique compared to recent models,with an accuracy of 99.37%.展开更多
This paper develops a real-time PV arrays maximum power harvesting scheme under partial shading condition(PSC)by reconfiguring PV arrays using Aquila optimizer(AO).AO is based on the natural behaviors of Aquila in cap...This paper develops a real-time PV arrays maximum power harvesting scheme under partial shading condition(PSC)by reconfiguring PV arrays using Aquila optimizer(AO).AO is based on the natural behaviors of Aquila in capturing prey,which can choose the best hunting mechanism ingeniously and quickly by balancing the local exploitation and global exploration via four hunting methods of Aquila:choosing the searching area through high soar with the vertical stoop,exploring in different searching spaces through contour flight with quick glide attack,exploiting in convergence searching space through low flight with slow attack,and swooping through walk and grabbing prey.In general,PV arrays reconfiguration is a problem of discrete optimization,thus a series of discrete operations are adopted in AO to enhance its optimization performance.Simulation results based on 10 cases under PSCs show that the mismatched power loss obtained by AO is the smallest compared with genetic algorithm,particle swarm optimization,ant colony algorithm,grasshopper optimization algorithm,and butterfly optimization algorithm,which reduced by 4.34%against butterfly optimization algorithm.展开更多
Using a time series method that combines both the persistent scatterer and small baseline approaches, we analyzed 9 scenes Envisat ASAR data over the L＇Aquila earthquake, and obtained a Shocke＇s displacement field a...Using a time series method that combines both the persistent scatterer and small baseline approaches, we analyzed 9 scenes Envisat ASAR data over the L＇Aquila earthquake, and obtained a Shocke＇s displacement field and its evolution processes. The results show that： （1） Envisat ASAR clearly detected the whole processes of displacement field of the L＇Aquila earthquake, and distinct variations at different stages of the displacement field. （2） Preseismic creep displacement → displacement mutation when faulting → constantly slowed down after the earthquake. （3） The area of the strongest deformation and ground rupture was a low-lying oval depression region to the southeast. Surface faulting within a zone of about 22 km× 14 km, with an orientation of 135°, occurred along the NW-striking and SW-dipping Paganica-S. Demetrio normal fault. （4） In analyzing an area of about 54 km x 59 km, bounded by north-south axis to the epicenter, the displacement field has significant characteristics of a watershed： westward of the epicenter shows uplift with maximum of 130 mm in line-of-sight （LOS）, and east of the epicenter was a region with 220 mm of maximum subsidence in the LOS, concentrating on the rupture zone, the majority of which formed in the course of faulting and subsequence.展开更多
In recent times,wireless sensor network(WSN)finds their suitability in several application areas,ranging from military to commercial ones.Since nodes in WSN are placed arbitrarily in the target field,node localization...In recent times,wireless sensor network(WSN)finds their suitability in several application areas,ranging from military to commercial ones.Since nodes in WSN are placed arbitrarily in the target field,node localization(NL)becomes essential where the positioning of the nodes can be determined by the aid of anchor nodes.The goal of any NL scheme is to improve the localization accuracy and reduce the localization error rate.With this motivation,this study focuses on the design of Intelligent Aquila Optimization Algorithm Based Node Localization Scheme(IAOAB-NLS)for WSN.The presented IAOAB-NLS model makes use of anchor nodes to determine proper positioning of the nodes.In addition,the IAOAB-NLS model is stimulated by the behaviour of Aquila.The IAOAB-NLS model has the ability to accomplish proper coordinate points of the nodes in the network.For guaranteeing the proficient NL process of the IAOAB-NLS model,widespread experimentation takes place to assure the betterment of the IAOAB-NLS model.The resultant values reported the effectual outcome of the IAOAB-NLS model irrespective of changing parameters in the network.展开更多
In this paper, we discuss a geographical methodology supported by specific geo-technologies which we are testing for the study of territories damaged by the L’Aquila earthquake of 6 April 2009 and which can be used i...In this paper, we discuss a geographical methodology supported by specific geo-technologies which we are testing for the study of territories damaged by the L’Aquila earthquake of 6 April 2009 and which can be used in similar situations. Subsequently, we provide an overview of the current situation and make a comparison between some aerial photographs obtained from an overflight in March 2012 and some photos made during our first field study in February 2010, in order to show the work undertaken or not during this period and to substantiate any considerations regarding the choices adopted and the necessary future planning. Moreover, we provide an example of the added value provided by the analysis of aerial photographs in both visible and thermal light for recognizing the provisional non-painted metal roofing of buildings in a post-earthquake urban area. In fact this technique can be useful for the rapid identification of damaged buildings and zones with provisional covering. In the present paper, we focus attention on L’Aquila town centre which provides a significant example of a “City of Stone” almost “minus” the presence of people.展开更多
The case in analysis is Santa Maria di Collemaggio, the church symbol of the town of L＇Aquila and the most important example of Romanesque style in Abruzzi, tragically damaged by the earthquake in 2009. The following...The case in analysis is Santa Maria di Collemaggio, the church symbol of the town of L＇Aquila and the most important example of Romanesque style in Abruzzi, tragically damaged by the earthquake in 2009. The following paper starts with an accurate analysis of the Basilica, whose historical, stylistical cultural characteristics make it an unicum in the whole urban environment. The authors tried to identify in which way these values have been compromised or altered after the earthquake through several analysis （surveys, historical researches etc.） aiming at the recognition of collapses, the cracks profile, the structural transformations caused by the provisional measures： the goal is to provide a kind of Basilica ＂cognitive manual＂ that will be useful for the future interventions. This first analysis allowed to understand many aspects： on the one hand, the constructive phases and which damages were caused by past careless interventions of restoration, drawing attention to the vulnerability elements of the Basilica; on the other hand, the innovative technologies and materials of the post-seismic provisional measures and their exact location.展开更多
基金funded by the Jiangxi Provincial Social Science Planning Project(21GL12)Jiangxi Provincial Higher Education Humanities and Social Sciences Planning Project(GL22232)Jiangxi Province College Students’Innovation and Entrepreneurship Training Program Project(S20241041027).
文摘Stereoscopic agriculture,as an advanced method of agricultural production,poses new challenges for multi-task trajectory planning of unmanned aerial vehicles(UAVs).To address the need for UAVs to perform multi-task trajectory planning in stereoscopic agriculture,a multi-task trajectory planning model and algorithm(IEP-AO)that synthesizes flight safety and flight efficiency is proposed.Based on the requirements of stereoscopic agricultural geomorphological features and operational characteristics,the multi-task trajectory planning model is ensured by constructing targeted constraints at five aspects,including the path,slope,altitude,corner,energy and obstacle threat,to improve the effectiveness of the trajectory planning model.And combined with the path optimization algorithm,an Aquila optimizer(IEP-AO)based on the interference-enhanced combination model is proposed,which can help UAVs to improve the trajectory search capability in complex operation space and large-scale operation tasks,and jump out of the locally optimal trajectory path region timely,to generate the optimal trajectory planning plan that can adapt to the diversity of the tasks and the flight efficiency.Meanwhile,four simulated flights with different operation scales and different scene constraints were conducted under the constructed real 3Dimension scene,and the experimental results can show that the proposedmulti-task trajectory planning method canmeet themulti-task requirements in stereoscopic agriculture and improve the mission execution efficiency and agricultural production effect of UAV.
基金funded by Taif University,Saudi Arabia,Project No.(TU-DSPP-2024-52).
文摘Aquila Optimizer(AO)is a recently proposed population-based optimization technique inspired by Aquila’s behavior in catching prey.AO is applied in various applications and its numerous variants were proposed in the literature.However,chaos theory has not been extensively investigated in AO.Moreover,it is still not applied in the parameter estimation of electro-hydraulic systems.In this work,ten well-defined chaotic maps were integrated into a narrowed exploitation of AO for the development of a robust chaotic optimization technique.An extensive investigation of twenty-three mathematical benchmarks and ten IEEE Congress on Evolutionary Computation(CEC)functions shows that chaotic Aquila optimization techniques perform better than the baseline technique.The investigation is further conducted on parameter estimation of an electro-hydraulic control system,which is performed on various noise levels and shows that the proposed chaotic AO with Piecewise map(CAO6)achieves the best fitness values of and at noise levels and respectively.Friedman test 2.873E-05,1.014E-04,8.728E-031.300E-03,1.300E-02,1.300E-01,for repeated measures,computational analysis,and Taguchi test reflect the superiority of CAO6 against the state of the arts,demonstrating its potential for addressing various engineering optimization problems.However,the sensitivity to parameter tuning may limit its direct application to complex optimization scenarios.
文摘This research study aims to enhance the optimization performance of a newly emerged Aquila Optimization algorithm by incorporating chaotic sequences rather than using uniformly generated Gaussian random numbers.This work employs 25 different chaotic maps under the framework of Aquila Optimizer.It considers the ten best chaotic variants for performance evaluation on multidimensional test functions composed of unimodal and multimodal problems,which have yet to be studied in past literature works.It was found that Ikeda chaotic map enhanced Aquila Optimization algorithm yields the best predictions and becomes the leading method in most of the cases.To test the effectivity of this chaotic variant on real-world optimization problems,it is employed on two constrained engineering design problems,and its effectiveness has been verified.Finally,phase equilibrium and semi-empirical parameter estimation problems have been solved by the proposed method,and respective solutions have been compared with those obtained from state-of-art optimizers.It is observed that CH01 can successfully cope with the restrictive nonlinearities and nonconvexities of parameter estimation and phase equilibrium problems,showing the capabilities of yielding minimum prediction error values of no more than 0.05 compared to the remaining algorithms utilized in the performance benchmarking process.
基金No.09FE3007 of Institute of Geophysics,China Earthquake Administration
文摘A Mw6.4 earthquake occurred in L＇Aquila, central Italy at 1：32：42 （UTC）, April 6, 2009. We quickly obtained the moment tensor solution of the earthquake by inverting the P waveforms of broadband recordings from the global seismographic network （GSN） stations using the quick technique of moment tensor inversion, and further inferred that the nodal plane of strike 132°, dip 53° and rake -103° is the seismogenic fault.
基金supported by National Natural Science Foundation of China(Grant No.62150410434)National Key Research and Development Program of China(Grant No.2019Y FB1405600)by LIESMARS Special Research Funding.
文摘Oil production estimation plays a critical role in economic plans for local governments and organizations.Therefore,many studies applied different Artificial Intelligence(AI)based meth-ods to estimate oil production in different countries.The Adaptive Neuro-Fuzzy Inference System(ANFIS)is a well-known model that has been successfully employed in various applica-tions,including time-series forecasting.However,the ANFIS model faces critical shortcomings in its parameters during the configuration process.From this point,this paper works to solve the drawbacks of the ANFIS by optimizing ANFIS parameters using a modified Aquila Optimizer(AO)with the Opposition-Based Learning(OBL)technique.The main idea of the developed model,AOOBL-ANFIS,is to enhance the search process of the AO and use the AOOBL to boost the performance of the ANFIS.The proposed model is evaluated using real-world oil produc-tion datasets collected from different oilfields using several performance metrics,including Root Mean Square Error(RMSE),Mean Absolute Error(MAE),coefficient of determination(R2),Standard Deviation(Std),and computational time.Moreover,the AOOBL-ANFIS model is compared to several modified ANFIS models include Particle Swarm Optimization(PSO)-ANFIS,Grey Wolf Optimizer(GWO)-ANFIS,Sine Cosine Algorithm(SCA)-ANFIS,Slime Mold Algorithm(SMA)-ANFIS,and Genetic Algorithm(GA)-ANFIS,respectively.Additionally,it is compared to well-known time series forecasting methods,namely,Autoregressive Integrated Moving Average(ARIMA),Long Short-Term Memory(LSTM),Seasonal Autoregressive Integrated Moving Average(SARIMA),and Neural Network(NN).The outcomes verified the high performance of the AOOBL-ANFIS,which outperformed the classic ANFIS model and the compared models.
基金Projects(40974006,40774003) supported by the National Natural Science Foundation of ChinaProject(NCET-08-0570) supported by the Program for New Century Excellent Talents in Chinese Universities+2 种基金Projects(2011JQ001,2009QZZD004) supported by the Fundamental Research Funds for the Central Universities in ChinaProjects(09K005,09K006) supported by the Key Laboratory for Precise Engineering Surveying & Hazard Monitoring of Hunan Province,ChinaProject(1343-74334000023) supported by the Graduate DegreeThesis Innovation Foundation of Central South University,China
文摘To better understand the mechanism of the Mw6.3 L＇Aquila （Central Italy） earthquake occurred in 2009, global positioning system （GPS） and interferometric synthetic aperture radar （InSAR） data were used to derive the coseismic slip distribution of the earthquake fault. Firstly, based on the homogeneous elastic half-space model, the fault geometric parameters were solved by the genetic algorithm. The best fitting model shows that the fault is a 13.7 km×14.1 km rectangular fault, in 139.3° strike direction and 50.2° southwest-dipping. Secondly, fixing the optimal fault geometric parameters, the fault plane was extended and discretized into 16× 16 patches, each with a size of 1 kmx 1 krn, and the non-uniform slip distribution of the fault was inverted by the steepest descent method with an appropriate smoothing ratio based on the layered crustal structure model. The preferred solution shows that the fault is mainly a normal fault with slight right-lateral strike slip, the maximum slip of 1.01 m is located in the depth of 8.28 km, the average rake is -100.9°, and the total geodetic moment is about 3.34× 1018 N.m （Mw 6.28）. The results are much closer than previous studies in comparison with the seismological estimation. These demonstrate that the coseismic fault slip distribution of the L＇Aauila earthauake inverted by the crustal model considering layered characters is reliable.
文摘In this work,we propose a real proportional-integral-derivative plus second-order derivative(PIDD2)controller as an efficient controller for vehicle cruise control systems to address the challenging issues related to efficient operation.In this regard,this paper is the first report in the literature demonstrating the implementation of a real PIDD2 controller for controlling the respective system.We construct a novel and efficient metaheuristic algorithm by improving the performance of the Aquila Optimizer via chaotic local search and modified opposition-based learning strategies and use it as an excellently performing tuning mechanism.We also propose a simple yet effective objective function to increase the performance of the proposed algorithm(CmOBL-AO)to adjust the real PIDD2 controller's parameters effectively.We show the CmOBL-AO algorithm to perform better than the differential evolution algorithm,gravitational search algorithm,African vultures optimization,and the Aquila Optimizer using well-known unimodal,multimodal benchmark functions.CEC2019 test suite is also used to perform ablation experiments to reveal the separate contributions of chaotic local search and modified opposition-based learning strategies to the CmOBL-AO algorithm.For the vehicle cruise control system,we confirm the more excellent performance of the proposed method against particle swarm,gray wolf,salp swarm,and original Aquila optimizers using statistical,Wilcoxon signed-rank,time response,robustness,and disturbance rejection analyses.We also use fourteen reported methods in the literature for the vehicle cruise control system to further verify the more promising performance of the CmOBL-AO-based real PIDD2 controller from a wider perspective.The excellent performance of the proposed method is also illustrated through different quality indicators and different operating speeds.Lastly,we also demonstrate the good performing capability of the CmOBL-AO algorithm for real traffic cases.We show the CmOBL-AO-based real PIDD2 controller as the most efficient method to control a vehicle cruise control system.
文摘Cyber-physical system(CPS)is a concept that integrates every computer-driven system interacting closely with its physical environment.Internet-of-things(IoT)is a union of devices and technologies that provide universal interconnection mechanisms between the physical and digital worlds.Since the complexity level of the CPS increases,an adversary attack becomes possible in several ways.Assuring security is a vital aspect of the CPS environment.Due to the massive surge in the data size,the design of anomaly detection techniques becomes a challenging issue,and domain-specific knowledge can be applied to resolve it.This article develops an Aquila Optimizer with Parameter Tuned Machine Learning Based Anomaly Detection(AOPTML-AD)technique in the CPS environment.The presented AOPTML-AD model intends to recognize and detect abnormal behaviour in the CPS environment.The presented AOPTML-AD framework initially pre-processes the network data by converting them into a compatible format.Besides,the improved Aquila optimization algorithm-based feature selection(IAOA-FS)algorithm is designed to choose an optimal feature subset.Along with that,the chimp optimization algorithm(ChOA)with an adaptive neuro-fuzzy inference system(ANFIS)model can be employed to recognise anomalies in the CPS environment.The ChOA is applied for optimal adjusting of the membership function(MF)indulged in the ANFIS method.The performance validation of the AOPTML-AD algorithm is carried out using the benchmark dataset.The extensive comparative study reported the better performance of the AOPTML-AD technique compared to recent models,with an accuracy of 99.37%.
基金supported by the Scientific Research Projects of Inner Mongolia Power(Group)Co.,Ltd.(Internal Electric Technology(2021)No.3).
文摘This paper develops a real-time PV arrays maximum power harvesting scheme under partial shading condition(PSC)by reconfiguring PV arrays using Aquila optimizer(AO).AO is based on the natural behaviors of Aquila in capturing prey,which can choose the best hunting mechanism ingeniously and quickly by balancing the local exploitation and global exploration via four hunting methods of Aquila:choosing the searching area through high soar with the vertical stoop,exploring in different searching spaces through contour flight with quick glide attack,exploiting in convergence searching space through low flight with slow attack,and swooping through walk and grabbing prey.In general,PV arrays reconfiguration is a problem of discrete optimization,thus a series of discrete operations are adopted in AO to enhance its optimization performance.Simulation results based on 10 cases under PSCs show that the mismatched power loss obtained by AO is the smallest compared with genetic algorithm,particle swarm optimization,ant colony algorithm,grasshopper optimization algorithm,and butterfly optimization algorithm,which reduced by 4.34%against butterfly optimization algorithm.
基金supported by Director Foundation of the Institute of Seismology,China Earthquake Administration(IS201266111)the Seism Science &Technology Spark Program of China Earthquake Administration(XH13036)Earthquake Industry Research Special Project(201308009)
文摘Using a time series method that combines both the persistent scatterer and small baseline approaches, we analyzed 9 scenes Envisat ASAR data over the L＇Aquila earthquake, and obtained a Shocke＇s displacement field and its evolution processes. The results show that： （1） Envisat ASAR clearly detected the whole processes of displacement field of the L＇Aquila earthquake, and distinct variations at different stages of the displacement field. （2） Preseismic creep displacement → displacement mutation when faulting → constantly slowed down after the earthquake. （3） The area of the strongest deformation and ground rupture was a low-lying oval depression region to the southeast. Surface faulting within a zone of about 22 km× 14 km, with an orientation of 135°, occurred along the NW-striking and SW-dipping Paganica-S. Demetrio normal fault. （4） In analyzing an area of about 54 km x 59 km, bounded by north-south axis to the epicenter, the displacement field has significant characteristics of a watershed： westward of the epicenter shows uplift with maximum of 130 mm in line-of-sight （LOS）, and east of the epicenter was a region with 220 mm of maximum subsidence in the LOS, concentrating on the rupture zone, the majority of which formed in the course of faulting and subsequence.
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work underGrant Number(RGP 1/322/42)PrincessNourah bint Abdulrahman UniversityResearchers Supporting Project number(PNURSP2022R303)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘In recent times,wireless sensor network(WSN)finds their suitability in several application areas,ranging from military to commercial ones.Since nodes in WSN are placed arbitrarily in the target field,node localization(NL)becomes essential where the positioning of the nodes can be determined by the aid of anchor nodes.The goal of any NL scheme is to improve the localization accuracy and reduce the localization error rate.With this motivation,this study focuses on the design of Intelligent Aquila Optimization Algorithm Based Node Localization Scheme(IAOAB-NLS)for WSN.The presented IAOAB-NLS model makes use of anchor nodes to determine proper positioning of the nodes.In addition,the IAOAB-NLS model is stimulated by the behaviour of Aquila.The IAOAB-NLS model has the ability to accomplish proper coordinate points of the nodes in the network.For guaranteeing the proficient NL process of the IAOAB-NLS model,widespread experimentation takes place to assure the betterment of the IAOAB-NLS model.The resultant values reported the effectual outcome of the IAOAB-NLS model irrespective of changing parameters in the network.
文摘In this paper, we discuss a geographical methodology supported by specific geo-technologies which we are testing for the study of territories damaged by the L’Aquila earthquake of 6 April 2009 and which can be used in similar situations. Subsequently, we provide an overview of the current situation and make a comparison between some aerial photographs obtained from an overflight in March 2012 and some photos made during our first field study in February 2010, in order to show the work undertaken or not during this period and to substantiate any considerations regarding the choices adopted and the necessary future planning. Moreover, we provide an example of the added value provided by the analysis of aerial photographs in both visible and thermal light for recognizing the provisional non-painted metal roofing of buildings in a post-earthquake urban area. In fact this technique can be useful for the rapid identification of damaged buildings and zones with provisional covering. In the present paper, we focus attention on L’Aquila town centre which provides a significant example of a “City of Stone” almost “minus” the presence of people.
文摘The case in analysis is Santa Maria di Collemaggio, the church symbol of the town of L＇Aquila and the most important example of Romanesque style in Abruzzi, tragically damaged by the earthquake in 2009. The following paper starts with an accurate analysis of the Basilica, whose historical, stylistical cultural characteristics make it an unicum in the whole urban environment. The authors tried to identify in which way these values have been compromised or altered after the earthquake through several analysis （surveys, historical researches etc.） aiming at the recognition of collapses, the cracks profile, the structural transformations caused by the provisional measures： the goal is to provide a kind of Basilica ＂cognitive manual＂ that will be useful for the future interventions. This first analysis allowed to understand many aspects： on the one hand, the constructive phases and which damages were caused by past careless interventions of restoration, drawing attention to the vulnerability elements of the Basilica; on the other hand, the innovative technologies and materials of the post-seismic provisional measures and their exact location.
