针对启发式算法在无人机不规则复杂地形和多重威胁环境下进行三维航迹规划时,存在路径波动大和优化性能不足的问题,提出结合高程数据的凸包策略以及一种改进的樽海鞘群算法(ISSA)。首先,基于ASTER GDEMV3和Open Street Map数据,构建杭...针对启发式算法在无人机不规则复杂地形和多重威胁环境下进行三维航迹规划时,存在路径波动大和优化性能不足的问题,提出结合高程数据的凸包策略以及一种改进的樽海鞘群算法(ISSA)。首先,基于ASTER GDEMV3和Open Street Map数据,构建杭州某处山区和纽约城市区域的高程模型;其次,结合地形高程信息,采用凸包策略编码并通过B样条曲线构建路径;最后,对樽海鞘群算法在个体位置更新公式上加入自适应Alpha稳定分布策略与非线性扰动策略,以平衡算法的全局开发能力与局部探索能力,并引入贪婪策略和鱼类聚集装置策略,提高算法搜索效率和精度。利用CEC2020测试函数对所提算法进行实验对比,验证了改进算法的性能。实验结果表明,凸包策略能有效提升算法规划能力,且与传统算法相比,改进后的算法能够使无人机的寻优精度更高,代价函数更小。展开更多
Blending is an important unit operation in process industry. Blending scheduling is nonlinear optimiza- tion problem with constraints. It is difficult to obtain optimum solution by other general optimization methods. ...Blending is an important unit operation in process industry. Blending scheduling is nonlinear optimiza- tion problem with constraints. It is difficult to obtain optimum solution by other general optimization methods. Particle swarm optimization (PSO) algorithm is developed for nonlinear optimization problems with both contin- uous and discrete variables. In order to obtain a global optimum solution quickly, PSO algorithm is applied to solve the problem of blending scheduling under uncertainty. The calculation results based on an example of gasoline blending agree satisfactory with the ideal values, which illustrates that the PSO algorithm is valid and effective in solving the blending scheduling problem.展开更多
Refineries often need to find similar crude oil to replace the scarce crude oil for stabilizing the feedstock property. We introduced the method for calculation of crude blended properties firstly, and then created a ...Refineries often need to find similar crude oil to replace the scarce crude oil for stabilizing the feedstock property. We introduced the method for calculation of crude blended properties firstly, and then created a crude oil selection and blending optimization model based on the data of crude oil property. The model is a mixed-integer nonlinear programming(MINLP) with constraints, and the target is to maximize the similarity between the blended crude oil and the objective crude oil. Furthermore, the model takes into account the selection of crude oils and their blending ratios simultaneously, and transforms the problem of looking for similar crude oil into the crude oil selection and blending optimization problem. We applied the Improved Cuckoo Search(ICS) algorithm to solving the model. Through the simulations, ICS was compared with the genetic algorithm, the particle swarm optimization algorithm and the CPLEX solver. The results show that ICS has very good optimization efficiency. The blending solution can provide a reference for refineries to find the similar crude oil. And the method proposed can also give some references to selection and blending optimization of other materials.展开更多
Optimization algorithms are applied to resolve the second-order pileup(SOP)issue from high counting rates occurring in digital alpha spectroscopy.These are antlion optimizer(ALO)and particle swarm optimization(PSO)alg...Optimization algorithms are applied to resolve the second-order pileup(SOP)issue from high counting rates occurring in digital alpha spectroscopy.These are antlion optimizer(ALO)and particle swarm optimization(PSO)algorithms.Both optimization algorithms are coupled to one of the three proposed peak finder algorithms.Three custom time-domain algorithms are proposed for retrieving SOP peaks,namely peak seek,slope tangent,and fast array algorithms.In addition,an average combinational algorithm is applied.The time occurrence of the retrieved peaks is tested for an elimination of illusive pulses.Conventional methods are inaccurate and timeconsuming.ALO and PSO optimizations are used for the localization of retrieved peaks.Optimum cost values that achieve the best fitness values are demonstrated.Thus,the optimum positions of the detected peak heights are achieved.Evaluation metrics of the optimized algorithms and their influences on the retrieved peaks parameters are established.Comparisons among such algorithms are investigated,and the algorithms are inspected in terms of their computational time and average error.The peak seek algorithm achieves the lowest average computational error for pulse parameters(amplitude and position).However,the fast array algorithm introduces the largest average error for pulse parameters.In addition,the peak seek algorithm coupled with an ALO or PSO algorithm is observed to realize a better performance in terms of the optimum cost and computational time.By contrast,the performance of the peak seek recovery algorithm is improved using the PSO.Furthermore,the computational time of the peak optimization using the PSO is much better than that of the ALO algorithm.As a final conclusion,the accuracy of the peaks detected by the PSO surpasses that for the peaks detected by the ALO.The implemented peak retrieval algorithms are validated through a comparison with experimental results from previous studies.The proposed algorithms achieve a notable precision for compensation of the SOP peaks within the alpha ray spectroscopy at a high counting rate.展开更多
In this paper,a genetic-algorithm-based artificial neural network(GAANN)model radioactivity prediction is proposed,which is verified by measuring results from Long Range Alpha Detector(LRAD).GAANN can integrate capabi...In this paper,a genetic-algorithm-based artificial neural network(GAANN)model radioactivity prediction is proposed,which is verified by measuring results from Long Range Alpha Detector(LRAD).GAANN can integrate capabilities of approximation of Artificial Neural Networks(ANN)and of global optimization of Genetic Algorithms(GA)so that the hybrid model can enhance capability of generalization and prediction accuracy,theoretically.With this model,both the number of hidden nodes and connection weights matrix in ANN are optimized using genetic operation.The real data sets are applied to the introduced method and the results are discussed and compared with the traditional Back Propagation(BP)neural network,showing the feasibility and validity of the proposed approach.展开更多
Rotor clearance is necessary for the safe operation of twin-screw compressors,and it has a major impact on the performance of twin-screw compressors.The purpose of this study was to obtain a rotor tooth profile with r...Rotor clearance is necessary for the safe operation of twin-screw compressors,and it has a major impact on the performance of twin-screw compressors.The purpose of this study was to obtain a rotor tooth profile with reasonable meshing clearance on the rotor end surface,so that the clearance on the rotor contact line would be uniform and the rotor could be smoothly meshed.Under ideal conditions,the rotor of a screw compressor should have no clearance or interference.However,owing to assembly errors,thermal compression,stress deformation,and other factors,a rotor without backlash modification will inevitably produce interference during operation.A new design method based on the Alpha shape solution was proposed to achieve an efficient and high-precision design of the clearance of the twin-screw rotor profile.This method avoids the complex analytical calculations in the traditional envelope principle.The best approximation of the points on the rotor conjugate motion sweeping surface in the points is illuminated using a specific color.The sweeping surface of the screw rotor single-tooth profile is roughly scanned to capture the base point set of the sweeping surface boundary points.The chord length and tilt angle of each interval are calculated using the value of the base point set to adjust the position,phase,and magnification of each interval sweeping surface.Finally,the data point set is converted to the same coordinate system to generate the conjugated rotor profile.An example was used to verify the feasibility and adaptability of this method.Based on the equidistant profile method,the clearance between male and female rotors of a screw compressor was obtained under actual operation conditions.Therefore,this study provides a basis for the meshing clearance design in the machining of twin-screw compressor rotors.展开更多
In medical science for envisaging human body’s phenomenal structure a major part has been driven by image processing techniques.Major objective of this work is to detect of cerebral atherosclerosis for image segmenta...In medical science for envisaging human body’s phenomenal structure a major part has been driven by image processing techniques.Major objective of this work is to detect of cerebral atherosclerosis for image segmentation applica-tion.Detection of some abnormal structures in human body has become a difficult task to complete with some simple images.For expounding and distinguishing neural architecture of human brain in an effective manner,MRI(Magnetic Reso-nance Imaging)is one of the most suitable and significant technique.Here we work on detection of Cerebral Atherosclerosis from MRI images of patients.Cer-ebral Atherosclerosis is a cerebral vascular disease causes narrowing of the arteries due to buildup of fatty plaque inside the blood vessels of the brain.It leads to Ischemic stroke if not diagnosed early.Stroke affects majorly old age people and percentage of affected women is more compared to men.Results:Preproces-sing is done by using alpha trimmed meanfilter which is used to remove noise and also it enhances the image.Segmentation of cerebral atherosclerosis is done by using K-means clustering,Contextual clustering,and proposed Hybrid algo-rithm.Various parameters like Correlation,Pixel density,energy is determined and from the analysis of parameters it is determined that proposed Hybrid algo-rithm is efficient.展开更多
As computers have become faster at performing computations over the decades, algorithms to play games have also become more efficient. This research paper seeks to see how the performance of the Minimax search evolves...As computers have become faster at performing computations over the decades, algorithms to play games have also become more efficient. This research paper seeks to see how the performance of the Minimax search evolves on increasing Connect-4 grid sizes. The objective of this study is to evaluate the effectiveness of the Minimax search algorithm in making optimal moves under different circumstances and to understand how well the algorithm scales. To answer this question we tested and analyzed the algorithm several times on different grid sizes with a time limit to see its performance as the complexity increases, we also looked for the average search depth for each grid size. The obtained results show that despite larger grid sizes, the Minimax search algorithm stays relatively consistent in terms of performance.展开更多
With the development of computer vision technology,panoramic image stitching has been widely used in fields such as scene reconstruction.A single traditional image cannot fully capture the panoramic view of the iconic...With the development of computer vision technology,panoramic image stitching has been widely used in fields such as scene reconstruction.A single traditional image cannot fully capture the panoramic view of the iconic East Gate of the South Campus of Shaanxi University of Technology.Therefore,this project aims to technically fuse multiple partial images into a complete panoramic image,enabling comprehensive recording and visual presentation of the architectural landscapes and spatial environments in this area.This report first introduces the technical background and application scenarios,clarifying the necessity of panoramic image stitching in campus landscape recording.It then elaborates on the core objectives and practical values,highlighting the role of technical solutions in improving image quality.Technically,a modular system design based on OpenCV is adopted,including modules such as image preprocessing,feature extraction and matching,image registration,fusion,and post-processing.Specifically,the SIFT algorithm is applied for feature extraction,KNN combined with ratio testing is used for feature matching,image registration is achieved by calculating the homography matrix,the fusion process utilizes multiband blending and Laplacian pyramid,and post-processing includes operations such as black area filling and CLAHE contrast enhancement.The experiment was conducted in a specific hardware and software environment using five overlapping images.After preprocessing,stitching,detail enhancement,and black edge repair,a panoramic image was successfully generated.The results show that the panoramic image fully presents the relevant scenery,with concealed seams,balanced exposure differences,and strong hierarchical details.This report provides a systematic description of the project’s technical implementation and achievement application.展开更多
文摘针对启发式算法在无人机不规则复杂地形和多重威胁环境下进行三维航迹规划时,存在路径波动大和优化性能不足的问题,提出结合高程数据的凸包策略以及一种改进的樽海鞘群算法(ISSA)。首先,基于ASTER GDEMV3和Open Street Map数据,构建杭州某处山区和纽约城市区域的高程模型;其次,结合地形高程信息,采用凸包策略编码并通过B样条曲线构建路径;最后,对樽海鞘群算法在个体位置更新公式上加入自适应Alpha稳定分布策略与非线性扰动策略,以平衡算法的全局开发能力与局部探索能力,并引入贪婪策略和鱼类聚集装置策略,提高算法搜索效率和精度。利用CEC2020测试函数对所提算法进行实验对比,验证了改进算法的性能。实验结果表明,凸包策略能有效提升算法规划能力,且与传统算法相比,改进后的算法能够使无人机的寻优精度更高,代价函数更小。
基金Supported by the National 863 Project (No. 2003AA412010) and the National 973 Program of China (No. 2002CB312201)
文摘Blending is an important unit operation in process industry. Blending scheduling is nonlinear optimiza- tion problem with constraints. It is difficult to obtain optimum solution by other general optimization methods. Particle swarm optimization (PSO) algorithm is developed for nonlinear optimization problems with both contin- uous and discrete variables. In order to obtain a global optimum solution quickly, PSO algorithm is applied to solve the problem of blending scheduling under uncertainty. The calculation results based on an example of gasoline blending agree satisfactory with the ideal values, which illustrates that the PSO algorithm is valid and effective in solving the blending scheduling problem.
基金supported by the National Natural Science Foundation of China(No.21365008)the Science Foundation of Guangxi province of China(No.2012GXNSFAA053230)
文摘Refineries often need to find similar crude oil to replace the scarce crude oil for stabilizing the feedstock property. We introduced the method for calculation of crude blended properties firstly, and then created a crude oil selection and blending optimization model based on the data of crude oil property. The model is a mixed-integer nonlinear programming(MINLP) with constraints, and the target is to maximize the similarity between the blended crude oil and the objective crude oil. Furthermore, the model takes into account the selection of crude oils and their blending ratios simultaneously, and transforms the problem of looking for similar crude oil into the crude oil selection and blending optimization problem. We applied the Improved Cuckoo Search(ICS) algorithm to solving the model. Through the simulations, ICS was compared with the genetic algorithm, the particle swarm optimization algorithm and the CPLEX solver. The results show that ICS has very good optimization efficiency. The blending solution can provide a reference for refineries to find the similar crude oil. And the method proposed can also give some references to selection and blending optimization of other materials.
文摘Optimization algorithms are applied to resolve the second-order pileup(SOP)issue from high counting rates occurring in digital alpha spectroscopy.These are antlion optimizer(ALO)and particle swarm optimization(PSO)algorithms.Both optimization algorithms are coupled to one of the three proposed peak finder algorithms.Three custom time-domain algorithms are proposed for retrieving SOP peaks,namely peak seek,slope tangent,and fast array algorithms.In addition,an average combinational algorithm is applied.The time occurrence of the retrieved peaks is tested for an elimination of illusive pulses.Conventional methods are inaccurate and timeconsuming.ALO and PSO optimizations are used for the localization of retrieved peaks.Optimum cost values that achieve the best fitness values are demonstrated.Thus,the optimum positions of the detected peak heights are achieved.Evaluation metrics of the optimized algorithms and their influences on the retrieved peaks parameters are established.Comparisons among such algorithms are investigated,and the algorithms are inspected in terms of their computational time and average error.The peak seek algorithm achieves the lowest average computational error for pulse parameters(amplitude and position).However,the fast array algorithm introduces the largest average error for pulse parameters.In addition,the peak seek algorithm coupled with an ALO or PSO algorithm is observed to realize a better performance in terms of the optimum cost and computational time.By contrast,the performance of the peak seek recovery algorithm is improved using the PSO.Furthermore,the computational time of the peak optimization using the PSO is much better than that of the ALO algorithm.As a final conclusion,the accuracy of the peaks detected by the PSO surpasses that for the peaks detected by the ALO.The implemented peak retrieval algorithms are validated through a comparison with experimental results from previous studies.The proposed algorithms achieve a notable precision for compensation of the SOP peaks within the alpha ray spectroscopy at a high counting rate.
基金Supported by National Natural Science Foundation of China(Nos.41025015,41104118,41274108,and 41274109)Special Program of Major Instruments of the Ministry of Science and Technology(No.2012YQ180118)+1 种基金Science and Technology Support Program of Sichuan Province(No.2013FZ0022)the Creative Team Program of Chengdu University of Technology(No.KYTD201301)
文摘In this paper,a genetic-algorithm-based artificial neural network(GAANN)model radioactivity prediction is proposed,which is verified by measuring results from Long Range Alpha Detector(LRAD).GAANN can integrate capabilities of approximation of Artificial Neural Networks(ANN)and of global optimization of Genetic Algorithms(GA)so that the hybrid model can enhance capability of generalization and prediction accuracy,theoretically.With this model,both the number of hidden nodes and connection weights matrix in ANN are optimized using genetic operation.The real data sets are applied to the introduced method and the results are discussed and compared with the traditional Back Propagation(BP)neural network,showing the feasibility and validity of the proposed approach.
文摘Rotor clearance is necessary for the safe operation of twin-screw compressors,and it has a major impact on the performance of twin-screw compressors.The purpose of this study was to obtain a rotor tooth profile with reasonable meshing clearance on the rotor end surface,so that the clearance on the rotor contact line would be uniform and the rotor could be smoothly meshed.Under ideal conditions,the rotor of a screw compressor should have no clearance or interference.However,owing to assembly errors,thermal compression,stress deformation,and other factors,a rotor without backlash modification will inevitably produce interference during operation.A new design method based on the Alpha shape solution was proposed to achieve an efficient and high-precision design of the clearance of the twin-screw rotor profile.This method avoids the complex analytical calculations in the traditional envelope principle.The best approximation of the points on the rotor conjugate motion sweeping surface in the points is illuminated using a specific color.The sweeping surface of the screw rotor single-tooth profile is roughly scanned to capture the base point set of the sweeping surface boundary points.The chord length and tilt angle of each interval are calculated using the value of the base point set to adjust the position,phase,and magnification of each interval sweeping surface.Finally,the data point set is converted to the same coordinate system to generate the conjugated rotor profile.An example was used to verify the feasibility and adaptability of this method.Based on the equidistant profile method,the clearance between male and female rotors of a screw compressor was obtained under actual operation conditions.Therefore,this study provides a basis for the meshing clearance design in the machining of twin-screw compressor rotors.
文摘In medical science for envisaging human body’s phenomenal structure a major part has been driven by image processing techniques.Major objective of this work is to detect of cerebral atherosclerosis for image segmentation applica-tion.Detection of some abnormal structures in human body has become a difficult task to complete with some simple images.For expounding and distinguishing neural architecture of human brain in an effective manner,MRI(Magnetic Reso-nance Imaging)is one of the most suitable and significant technique.Here we work on detection of Cerebral Atherosclerosis from MRI images of patients.Cer-ebral Atherosclerosis is a cerebral vascular disease causes narrowing of the arteries due to buildup of fatty plaque inside the blood vessels of the brain.It leads to Ischemic stroke if not diagnosed early.Stroke affects majorly old age people and percentage of affected women is more compared to men.Results:Preproces-sing is done by using alpha trimmed meanfilter which is used to remove noise and also it enhances the image.Segmentation of cerebral atherosclerosis is done by using K-means clustering,Contextual clustering,and proposed Hybrid algo-rithm.Various parameters like Correlation,Pixel density,energy is determined and from the analysis of parameters it is determined that proposed Hybrid algo-rithm is efficient.
文摘As computers have become faster at performing computations over the decades, algorithms to play games have also become more efficient. This research paper seeks to see how the performance of the Minimax search evolves on increasing Connect-4 grid sizes. The objective of this study is to evaluate the effectiveness of the Minimax search algorithm in making optimal moves under different circumstances and to understand how well the algorithm scales. To answer this question we tested and analyzed the algorithm several times on different grid sizes with a time limit to see its performance as the complexity increases, we also looked for the average search depth for each grid size. The obtained results show that despite larger grid sizes, the Minimax search algorithm stays relatively consistent in terms of performance.
文摘With the development of computer vision technology,panoramic image stitching has been widely used in fields such as scene reconstruction.A single traditional image cannot fully capture the panoramic view of the iconic East Gate of the South Campus of Shaanxi University of Technology.Therefore,this project aims to technically fuse multiple partial images into a complete panoramic image,enabling comprehensive recording and visual presentation of the architectural landscapes and spatial environments in this area.This report first introduces the technical background and application scenarios,clarifying the necessity of panoramic image stitching in campus landscape recording.It then elaborates on the core objectives and practical values,highlighting the role of technical solutions in improving image quality.Technically,a modular system design based on OpenCV is adopted,including modules such as image preprocessing,feature extraction and matching,image registration,fusion,and post-processing.Specifically,the SIFT algorithm is applied for feature extraction,KNN combined with ratio testing is used for feature matching,image registration is achieved by calculating the homography matrix,the fusion process utilizes multiband blending and Laplacian pyramid,and post-processing includes operations such as black area filling and CLAHE contrast enhancement.The experiment was conducted in a specific hardware and software environment using five overlapping images.After preprocessing,stitching,detail enhancement,and black edge repair,a panoramic image was successfully generated.The results show that the panoramic image fully presents the relevant scenery,with concealed seams,balanced exposure differences,and strong hierarchical details.This report provides a systematic description of the project’s technical implementation and achievement application.
