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Optimizing Deep Learning for Computer-Aided Diagnosis of Lung Diseases: An Automated Method Combining Evolutionary Algorithm, Transfer Learning, and Model Compression
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作者 Hassen Louati Ali Louati +1 位作者 Elham Kariri Slim Bechikh 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第3期2519-2547,共29页
Recent developments in Computer Vision have presented novel opportunities to tackle complex healthcare issues,particularly in the field of lung disease diagnosis.One promising avenue involves the use of chest X-Rays,w... Recent developments in Computer Vision have presented novel opportunities to tackle complex healthcare issues,particularly in the field of lung disease diagnosis.One promising avenue involves the use of chest X-Rays,which are commonly utilized in radiology.To fully exploit their potential,researchers have suggested utilizing deep learning methods to construct computer-aided diagnostic systems.However,constructing and compressing these systems presents a significant challenge,as it relies heavily on the expertise of data scientists.To tackle this issue,we propose an automated approach that utilizes an evolutionary algorithm(EA)to optimize the design and compression of a convolutional neural network(CNN)for X-Ray image classification.Our approach accurately classifies radiography images and detects potential chest abnormalities and infections,including COVID-19.Furthermore,our approach incorporates transfer learning,where a pre-trainedCNNmodel on a vast dataset of chest X-Ray images is fine-tuned for the specific task of detecting COVID-19.This method can help reduce the amount of labeled data required for the task and enhance the overall performance of the model.We have validated our method via a series of experiments against state-of-the-art architectures. 展开更多
关键词 Computer-aided diagnosis deep learning evolutionary algorithms deep compression transfer learning
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Uniaxial Compressive Strength Prediction for Rock Material in Deep Mine Using Boosting-Based Machine Learning Methods and Optimization Algorithms
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作者 Junjie Zhao Diyuan Li +1 位作者 Jingtai Jiang Pingkuang Luo 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第7期275-304,共30页
Traditional laboratory tests for measuring rock uniaxial compressive strength(UCS)are tedious and timeconsuming.There is a pressing need for more effective methods to determine rock UCS,especially in deep mining envir... Traditional laboratory tests for measuring rock uniaxial compressive strength(UCS)are tedious and timeconsuming.There is a pressing need for more effective methods to determine rock UCS,especially in deep mining environments under high in-situ stress.Thus,this study aims to develop an advanced model for predicting the UCS of rockmaterial in deepmining environments by combining three boosting-basedmachine learning methods with four optimization algorithms.For this purpose,the Lead-Zinc mine in Southwest China is considered as the case study.Rock density,P-wave velocity,and point load strength index are used as input variables,and UCS is regarded as the output.Subsequently,twelve hybrid predictive models are obtained.Root mean square error(RMSE),mean absolute error(MAE),coefficient of determination(R2),and the proportion of the mean absolute percentage error less than 20%(A-20)are selected as the evaluation metrics.Experimental results showed that the hybridmodel consisting of the extreme gradient boostingmethod and the artificial bee colony algorithm(XGBoost-ABC)achieved satisfactory results on the training dataset and exhibited the best generalization performance on the testing dataset.The values of R2,A-20,RMSE,and MAE on the training dataset are 0.98,1.0,3.11 MPa,and 2.23MPa,respectively.The highest values of R2 and A-20(0.93 and 0.96),and the smallest RMSE and MAE values of 4.78 MPa and 3.76MPa,are observed on the testing dataset.The proposed hybrid model can be considered a reliable and effective method for predicting rock UCS in deep mines. 展开更多
关键词 Uniaxial compression strength strength prediction machine learning optimization algorithm
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Lossless embedding: A visually meaningful image encryption algorithm based on hyperchaos and compressive sensing 被引量:1
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作者 王兴元 王哓丽 +2 位作者 滕琳 蒋东华 咸永锦 《Chinese Physics B》 SCIE EI CAS CSCD 2023年第2期136-149,共14页
A novel visually meaningful image encryption algorithm is proposed based on a hyperchaotic system and compressive sensing(CS), which aims to improve the visual security of steganographic image and decrypted quality. F... A novel visually meaningful image encryption algorithm is proposed based on a hyperchaotic system and compressive sensing(CS), which aims to improve the visual security of steganographic image and decrypted quality. First, a dynamic spiral block scrambling is designed to encrypt the sparse matrix generated by performing discrete wavelet transform(DWT)on the plain image. Then, the encrypted image is compressed and quantified to obtain the noise-like cipher image. Then the cipher image is embedded into the alpha channel of the carrier image in portable network graphics(PNG) format to generate the visually meaningful steganographic image. In our scheme, the hyperchaotic Lorenz system controlled by the hash value of plain image is utilized to construct the scrambling matrix, the measurement matrix and the embedding matrix to achieve higher security. In addition, compared with other existing encryption algorithms, the proposed PNG-based embedding method can blindly extract the cipher image, thus effectively reducing the transmission cost and storage space. Finally, the experimental results indicate that the proposed encryption algorithm has very high visual security. 展开更多
关键词 chaotic image encryption compressive sensing meaningful cipher image portable network graphics image encryption algorithm
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A hybrid quantum encoding algorithm of vector quantization for image compression 被引量:4
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作者 庞朝阳 周正威 郭光灿 《Chinese Physics B》 SCIE EI CAS CSCD 2006年第12期3039-3043,共5页
Many classical encoding algorithms of vector quantization (VQ) of image compression that can obtain global optimal solution have computational complexity O(N). A pure quantum VQ encoding algorithm with probability... Many classical encoding algorithms of vector quantization (VQ) of image compression that can obtain global optimal solution have computational complexity O(N). A pure quantum VQ encoding algorithm with probability of success near 100% has been proposed, that performs operations 45√N times approximately. In this paper, a hybrid quantum VQ encoding algorithm between the classical method and the quantum algorithm is presented. The number of its operations is less than √N for most images, and it is more efficient than the pure quantum algorithm. 展开更多
关键词 vector quantization Grover's algorithm image compression quantum algorithm
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Design of quantum VQ iteration and quantum VQ encoding algorithm taking O(√N) steps for data compression 被引量:2
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作者 庞朝阳 周正威 +1 位作者 陈平形 郭光灿 《Chinese Physics B》 SCIE EI CAS CSCD 2006年第3期618-623,共6页
Vector quantization (VQ) is an important data compression method. The key of the encoding of VQ is to find the closest vector among N vectors for a feature vector. Many classical linear search algorithms take O(N)... Vector quantization (VQ) is an important data compression method. The key of the encoding of VQ is to find the closest vector among N vectors for a feature vector. Many classical linear search algorithms take O(N) steps of distance computing between two vectors. The quantum VQ iteration and corresponding quantum VQ encoding algorithm that takes O(√N) steps are presented in this paper. The unitary operation of distance computing can be performed on a number of vectors simultaneously because the quantum state exists in a superposition of states. The quantum VQ iteration comprises three oracles, by contrast many quantum algorithms have only one oracle, such as Shor's factorization algorithm and Grover's algorithm. Entanglement state is generated and used, by contrast the state in Grover's algorithm is not an entanglement state. The quantum VQ iteration is a rotation over subspace, by contrast the Grover iteration is a rotation over global space. The quantum VQ iteration extends the Grover iteration to the more complex search that requires more oracles. The method of the quantum VQ iteration is universal. 展开更多
关键词 data compression vector quantization Grover's algorithm quantum VQ iteration
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Design of real-time data compression wireless sensor network based on LZW algorithm 被引量:2
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作者 CHENG Ya-li LI Jin-ming CHENG Nai-peng 《Journal of Measurement Science and Instrumentation》 CAS CSCD 2019年第2期191-198,共8页
A real-time data compression wireless sensor network based on Lempel-Ziv-Welch encoding(LZW)algorithm is designed for the increasing data volume of terminal nodes when using ZigBee for long-distance wireless communica... A real-time data compression wireless sensor network based on Lempel-Ziv-Welch encoding(LZW)algorithm is designed for the increasing data volume of terminal nodes when using ZigBee for long-distance wireless communication.The system consists of a terminal node,a router,a coordinator,and an upper computer.The terminal node is responsible for storing and sending the collected data after the LZW compression algorithm is compressed;The router is responsible for the relay of data in the wireless network;The coordinator is responsible for sending the received data to the upper computer.In terms of network function realization,the development and configuration of CC2530 chips on terminal nodes,router nodes,and coordinator nodes are completed using the Z-stack protocol stack,and the network is successfully organized.Through the final simulation analysis and test verification,the system realizes the wireless acquisition and storage of remote data,and reduces the network occupancy rate through the data compression,which has a certain practical value and application prospects. 展开更多
关键词 wireless sensor network ZIGBEE LZW algorithm data compression
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Secure Transmission of Compressed Medical Image Sequences on Communication Networks Using Motion Vector Watermarking
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作者 Rafi Ullah Mohd Hilmi bin Hasan +1 位作者 Sultan Daud Khan Mussadiq Abdul Rahim 《Computers, Materials & Continua》 SCIE EI 2024年第3期3283-3301,共19页
Medical imaging plays a key role within modern hospital management systems for diagnostic purposes.Compression methodologies are extensively employed to mitigate storage demands and enhance transmission speed,all whil... Medical imaging plays a key role within modern hospital management systems for diagnostic purposes.Compression methodologies are extensively employed to mitigate storage demands and enhance transmission speed,all while upholding image quality.Moreover,an increasing number of hospitals are embracing cloud computing for patient data storage,necessitating meticulous scrutiny of server security and privacy protocols.Nevertheless,considering the widespread availability of multimedia tools,the preservation of digital data integrity surpasses the significance of compression alone.In response to this concern,we propose a secure storage and transmission solution for compressed medical image sequences,such as ultrasound images,utilizing a motion vector watermarking scheme.The watermark is generated employing an error-correcting code known as Bose-Chaudhuri-Hocquenghem(BCH)and is subsequently embedded into the compressed sequence via block-based motion vectors.In the process of watermark embedding,motion vectors are selected based on their magnitude and phase angle.When embedding watermarks,no specific spatial area,such as a region of interest(ROI),is used in the images.The embedding of watermark bits is dependent on motion vectors.Although reversible watermarking allows the restoration of the original image sequences,we use the irreversible watermarking method.The reason for this is that the use of reversible watermarks may impede the claims of ownership and legal rights.The restoration of original data or images may call into question ownership or other legal claims.The peak signal-to-noise ratio(PSNR)and structural similarity index(SSIM)serve as metrics for evaluating the watermarked image quality.Across all images,the PSNR value exceeds 46 dB,and the SSIM value exceeds 0.92.Experimental results substantiate the efficacy of the proposed technique in preserving data integrity. 展开更多
关键词 Block matching algorithm(BMA) compression full-search algorithm motion vectors ultrasound image sequence WATERMARKING
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Curvature Quantified Douglas-Peucker-based Phasor Measurement Unit Data Compression Method for Power System Situational Awareness
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作者 Weitao Tan Tianhan Zhang +3 位作者 Yuanqian Ma Shengyuan Liu Li Yang Zhenzhi Lin 《Protection and Control of Modern Power Systems》 SCIE EI 2024年第2期128-137,共10页
Facing constraints imposed by storage and bandwidth limitations,the vast volume of phasor meas-urement unit(PMU)data collected by the wide-area measurement system(WAMS)for power systems cannot be fully utilized.This l... Facing constraints imposed by storage and bandwidth limitations,the vast volume of phasor meas-urement unit(PMU)data collected by the wide-area measurement system(WAMS)for power systems cannot be fully utilized.This limitation significantly hinders the effective deployment of situational awareness technologies for systematic applications.In this work,an effective curvature quantified Douglas-Peucker(CQDP)-based PMU data compression method is proposed for situational awareness of power systems.First,a curvature integrated distance(CID)for measuring the local flection and fluc-tuation of PMU signals is developed.The Doug-las-Peucker(DP)algorithm integrated with a quan-tile-based parameter adaptation scheme is then proposed to extract feature points for profiling the trends within the PMU signals.This allows adaptive adjustment of the al-gorithm parameters,so as to maintain the desired com-pression ratio and reconstruction accuracy as much as possible,irrespective of the power system dynamics.Fi-nally,case studies on the Western Electricity Coordinat-ing Council(WECC)179-bus system and the actual Guangdong power system are performed to verify the effectiveness of the proposed method.The simulation results show that the proposed method achieves stably higher compression ratio and reconstruction accuracy in both steady state and in transients of the power system,and alleviates the compression performance degradation problem faced by existing compression methods.Index Terms—Curvature quantified Douglas-Peucker,data compression,phasor measurement unit,power sys-tem situational awareness. 展开更多
关键词 Curvature quantified douglas-peucker data compression phasor measurement unit power sys-tem situational awareness
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An image joint compression-encryption algorithm based on adaptive arithmetic coding
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作者 邓家先 邓海涛 《Chinese Physics B》 SCIE EI CAS CSCD 2013年第9期403-408,共6页
Through a series of studies on arithmetic coding and arithmetic encryption, a novel image joint compression- encryption algorithm based on adaptive arithmetic coding is proposed. The contexts produced in the process o... Through a series of studies on arithmetic coding and arithmetic encryption, a novel image joint compression- encryption algorithm based on adaptive arithmetic coding is proposed. The contexts produced in the process of image compression are modified by keys in order to achieve image joint compression encryption. Combined with the bit-plane coding technique, the discrete wavelet transform coefficients in different resolutions can be encrypted respectively with different keys, so that the resolution selective encryption is realized to meet different application needs. Zero-tree coding is improved, and adaptive arithmetic coding is introduced. Then, the proposed joint compression-encryption algorithm is simulated. The simulation results show that as long as the parameters are selected appropriately, the compression efficiency of proposed image joint compression-encryption algorithm is basically identical to that of the original image compression algorithm, and the security of the proposed algorithm is better than the joint encryption algorithm based on interval splitting. 展开更多
关键词 image compression joint compression-encryption algorithm arithmetic encryption progressiveclassification encryption
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Optimal Configuration of Fault Location Measurement Points in DC Distribution Networks Based on Improved Particle Swarm Optimization Algorithm
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作者 Huanan Yu Hangyu Li +1 位作者 He Wang Shiqiang Li 《Energy Engineering》 EI 2024年第6期1535-1555,共21页
The escalating deployment of distributed power sources and random loads in DC distribution networks hasamplified the potential consequences of faults if left uncontrolled. To expedite the process of achieving an optim... The escalating deployment of distributed power sources and random loads in DC distribution networks hasamplified the potential consequences of faults if left uncontrolled. To expedite the process of achieving an optimalconfiguration of measurement points, this paper presents an optimal configuration scheme for fault locationmeasurement points in DC distribution networks based on an improved particle swarm optimization algorithm.Initially, a measurement point distribution optimization model is formulated, leveraging compressive sensing.The model aims to achieve the minimum number of measurement points while attaining the best compressivesensing reconstruction effect. It incorporates constraints from the compressive sensing algorithm and networkwide viewability. Subsequently, the traditional particle swarm algorithm is enhanced by utilizing the Haltonsequence for population initialization, generating uniformly distributed individuals. This enhancement reducesindividual search blindness and overlap probability, thereby promoting population diversity. Furthermore, anadaptive t-distribution perturbation strategy is introduced during the particle update process to enhance the globalsearch capability and search speed. The established model for the optimal configuration of measurement points issolved, and the results demonstrate the efficacy and practicality of the proposed method. The optimal configurationreduces the number of measurement points, enhances localization accuracy, and improves the convergence speedof the algorithm. These findings validate the effectiveness and utility of the proposed approach. 展开更多
关键词 Optimal allocation improved particle swarm algorithm fault location compressed sensing DC distribution network
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A Bit-level Text Compression Scheme Based on the ACW Algorithm
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作者 Hussein Al-Bahadili Shakir M. Hussain 《International Journal of Automation and computing》 EI 2010年第1期123-131,共9页
This paper presents a description and performance evaluation of a new bit-level, lossless, adaptive, and asymmetric data compression scheme that is based on the adaptive character wordlength (ACW(n)) algorithm. Th... This paper presents a description and performance evaluation of a new bit-level, lossless, adaptive, and asymmetric data compression scheme that is based on the adaptive character wordlength (ACW(n)) algorithm. The proposed scheme enhances the compression ratio of the ACW(n) algorithm by dividing the binary sequence into a number of subsequences (s), each of them satisfying the condition that the number of decimal values (d) of the n-bit length characters is equal to or less than 256. Therefore, the new scheme is referred to as ACW(n, s), where n is the adaptive character wordlength and s is the number of subsequences. The new scheme was used to compress a number of text files from standard corpora. The obtained results demonstrate that the ACW(n, s) scheme achieves higher compression ratio than many widely used compression algorithms and it achieves a competitive performance compared to state-of-the-art compression tools. 展开更多
关键词 Data compression bit-level text compression ACW(n) algorithm Huffman coding adaptive coding
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PERFORMANCE COMPARISON OF ECG COMPRESSION ALGORITHMS BASED ON CLINICAL DIAGNOSIS
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作者 李顺山 李高平 +1 位作者 乐园 庄天戈 《Journal of Shanghai Jiaotong university(Science)》 EI 2001年第1期21-26,共6页
This paper reviewed the recent progress in the field of electrocardiogram (ECG) compression and compared the efficiency of some compression algorithms. By experimenting on the 500 cases of ECG signals from the ECG dat... This paper reviewed the recent progress in the field of electrocardiogram (ECG) compression and compared the efficiency of some compression algorithms. By experimenting on the 500 cases of ECG signals from the ECG database of China, it obtained the numeral indexes for each algorithm. Then by using the automatic diagnostic program developed by Shanghai Zhongshan Hospital, it also got the parameters of the reconstructed signals from linear approximation distance threshold (LADT), wavelet transform (WT), differential pulse code modulation (DPCM) and discrete cosine transform (DCT) algorithm. The results show that when the index of percent of root mean square difference(PRD) is less than 2.5%, the diagnostic agreement ratio is more than 90%; the index of PRD cannot completely show the damage of significant clinical information; the performance of wavelet algorithm exceeds other methods in the same compression ratio (CR). For the statistical result of the parameters of various methods and the clinical diagnostic results, it is of certain value and originality in the field of ECG compression research. 展开更多
关键词 compression algorithms performance comparison clinical diagnosis
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The Compression Algorithm for the Data Acquisition System in HT-7 Tokamak
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作者 朱琳 罗家融 +1 位作者 李贵明 岳冬利 《Plasma Science and Technology》 SCIE EI CAS CSCD 2003年第5期1939-1944,共6页
HT-7 superconducting tokamak in the Institute of Plasma Physics of the Chinese Academy of Sciences is an experimental device for fusion research in China. The main task of the data acquisition system of HT-7 is to acq... HT-7 superconducting tokamak in the Institute of Plasma Physics of the Chinese Academy of Sciences is an experimental device for fusion research in China. The main task of the data acquisition system of HT-7 is to acquire, store, analyze and index the data. The volume of the data is nearly up to hundreds of million bytes. Besides the hardware and software support, a great capacity of data storage, process and transfer is a more important problem. To deal with this problem, the key technology is data compression algorithm. In the paper, the data format in HT-7 is introduced first, then the data compression algorithm, LZO, being a kind of portable lossless data compression algorithm with ANSI C, is analyzed. This compression algorithm, which fits well with the data acquisition and distribution in the nuclear fusion experiment, offers a pretty fast compression and extremely fast decompression. At last the performance evaluation of LZO application in HT-7 is given. 展开更多
关键词 data compression algorithm HT-7 tokamak
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Computer Desktop Image Compression Technology Based on the Clustering Algorithm
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作者 LIU Fei 《International English Education Research》 2019年第2期33-35,共3页
The clustering algorithm has a very important application in the data mining technology,and can achieve good results in the data classification operation.With the rapid development of the network communication technol... The clustering algorithm has a very important application in the data mining technology,and can achieve good results in the data classification operation.With the rapid development of the network communication technology and the personal computers and other digital devices,the real-time computer desktop image transmission technology has been widely used.The computer desktop image compression algorithm based on the block classification can effectively realize the compression and storage of the computer desktop images,and significantly improve the speed and quality of the computer desktop image transmission. 展开更多
关键词 CLUSTERING algorithm COMPUTER DESKTOP image compression TECHNOLOGY
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The Application Research of a Fast Recursive Predictive Algorithm on Medical X-ray Image Compression
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作者 LIU Wen-sheng1,JIANG Da-zong21 The Science and Technology Division of Tianjin Economy Committee, Tianjin 300040,China 2 The BME Institute of Xian Jiaotong University, Xian 710049,China 《Chinese Journal of Biomedical Engineering(English Edition)》 2003年第2期72-79,共8页
This paper studied a fast recursive predictive algorithm used for medical X-ray image compression. This algorithm consists of mathematics model building, fast recursive algorithm deducing, initial value determining, s... This paper studied a fast recursive predictive algorithm used for medical X-ray image compression. This algorithm consists of mathematics model building, fast recursive algorithm deducing, initial value determining, step-size selecting, image compression encoding and original image recovering. The experiment result indicates that this algorithm has not only a higher compression ratio to medical X-ray images compression, but also promotes image compression speed greatly. 展开更多
关键词 FAST RECURSIVE PREDICTIVE algorithm IMAGE compression
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基于Douglas-Peucker算法的船舶AIS航迹数据压缩 被引量:23
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作者 张树凯 刘正江 +2 位作者 张显库 史国友 蔡垚 《哈尔滨工程大学学报》 EI CAS CSCD 北大核心 2015年第5期595-599,共5页
为解决普通模式下,将海量AIS航迹数据显示在ECDIS平台上效率低、实时性差等问题,设计一种基于DouglasPeucker算法的AIS航迹数据压缩算法。通过分析AIS航迹数据的特征,总结普通模式下ECDIS平台AIS航迹显示实时性差的原因,提出在保留原始... 为解决普通模式下,将海量AIS航迹数据显示在ECDIS平台上效率低、实时性差等问题,设计一种基于DouglasPeucker算法的AIS航迹数据压缩算法。通过分析AIS航迹数据的特征,总结普通模式下ECDIS平台AIS航迹显示实时性差的原因,提出在保留原始航迹特征和误差允许的范围内剔除冗余和重复信息的思想,结合Douglas-Peucker算法,根据设定的不同阈值提取出关键特征点从而对AIS航迹数据进行压缩。在VC2010平台下对该算法进行实现,实践证明,该算法能在较低失真度的前提下对船舶AIS航迹数据进行压缩,提高了轨迹回放、再现效率,与普通模式下ECDIS显示大量AIS航迹相比,系统占用资源少、处理效率高并具有较高的稳定性。 展开更多
关键词 船舶 AIS航迹 douglas-peucker算法 数据压缩
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Douglas-Peucker算法在无拓扑矢量数据压缩中的新改进 被引量:16
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作者 谢亦才 林渝淇 李岩 《计算机应用与软件》 CSCD 2010年第1期141-144,共4页
分析常规Douglas-Peucker算法压缩无拓扑矢量数据时产生公共边"裂缝"现象的原因——公共边被两次或可能更多次压缩,而每次运用Douglas-Peucker算法压缩时所选择的初始点和终点不同造成的。为此,提出公共边对象化Douglas-Peuc... 分析常规Douglas-Peucker算法压缩无拓扑矢量数据时产生公共边"裂缝"现象的原因——公共边被两次或可能更多次压缩,而每次运用Douglas-Peucker算法压缩时所选择的初始点和终点不同造成的。为此,提出公共边对象化Douglas-Peucker改进算法。为实现此算法,首先设计了新的公共边提取算法来提取公共边,然后使用OOP技术,把公共边的相关信息封装成类,最后根据公共边对象提供的信息对多边形的公共边和非公共边分别进行Douglas-Peucker压缩。以广东省行政界线的SVG矢量图为实验对象验证了此算法的有效性,分析了本算法相对于其它Douglas-Peucker改进算法在所需辅助空间和时间效率上的优势。 展开更多
关键词 douglas-peucker算法 矢量数据压缩 SVG 公共边对象化douglas-peucker改进算法
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Douglas-Peucker算法在无拓扑矢量数据压缩中的改进 被引量:11
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作者 谢亦才 李岩 《计算机工程与应用》 CSCD 北大核心 2009年第32期189-192,共4页
分析了常规Douglas-Peucker算法压缩无拓扑矢量数据时产生公共边"裂缝"现象的原因,即公共边被两次或可能更多次压缩,而每次运用Douglas-Peucker算法压缩时所选择的初始点和终点不同造成的。为此,提出了公共边对象化Douglas-Pe... 分析了常规Douglas-Peucker算法压缩无拓扑矢量数据时产生公共边"裂缝"现象的原因,即公共边被两次或可能更多次压缩,而每次运用Douglas-Peucker算法压缩时所选择的初始点和终点不同造成的。为此,提出了公共边对象化Douglas-Peucker改进算法。为实现此算法,首先设计了新的公共边提取算法来提取公共边,然后使用OOP技术,把公共边的相关信息封装成类,最后根据公共边对象提供的信息对多边形的公共边和非公共边分别进行Douglas-Peucker压缩。以广东省行政界线的SVG矢量图为实验对象验证了该算法的有效性,分析了该算法相对于其他Douglas-Peucker改进算法在所需辅助空间和时间效率上的优势。 展开更多
关键词 douglas-peucker算法 矢量数据压缩 可缩放矢量图形(SVG) 公共边对象化Douglas—Peucker改进算法
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COMPRESSIBLE VIRTUAL WINDOW ALGORITHM IN PICKING PROCESS CONTROL OF AUTOMATED SORTING SYSTEM 被引量:15
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作者 WU Yaohua ZHANG Yigong WU Yingying 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2008年第3期41-45,共5页
Compared to fixed virtual window algorithm (FVWA), the dynamic virtual window algorithm (DVWA) determines the length of each virtual container according to the sizes of goods of each order, which saves space of vi... Compared to fixed virtual window algorithm (FVWA), the dynamic virtual window algorithm (DVWA) determines the length of each virtual container according to the sizes of goods of each order, which saves space of virtual containers and improves the picking efficiency. However, the interval of consecutive goods caused by dispensers on conveyor can not be eliminated by DVWA, which limits a further improvement of picking efficiency. In order to solve this problem, a compressible virtual window algorithm (CVWA) is presented. It not only inherits the merit of DVWA but also compresses the length of virtual containers without congestion of order accumulation by advancing the beginning time of order picking and reasonably coordinating the pace of order accumulation. The simulation result proves that the picking efficiency of automated sorting system is greatly improved by CVWA. 展开更多
关键词 Virtual window algorithm Dynamics compressIBILITY Picking efficiency
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Intelligent modelling of clay compressibility using hybrid meta-heuristic and machine learning algorithms 被引量:7
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作者 Pin Zhang Zhen-Yu Yin +2 位作者 Yin-Fu Jin Tommy HTChan Fu-Ping Gao 《Geoscience Frontiers》 SCIE CAS CSCD 2021年第1期441-452,共12页
Compression index Ccis an essential parameter in geotechnical design for which the effectiveness of correlation is still a challenge.This paper suggests a novel modelling approach using machine learning(ML)technique.T... Compression index Ccis an essential parameter in geotechnical design for which the effectiveness of correlation is still a challenge.This paper suggests a novel modelling approach using machine learning(ML)technique.The performance of five commonly used machine learning(ML)algorithms,i.e.back-propagation neural network(BPNN),extreme learning machine(ELM),support vector machine(SVM),random forest(RF)and evolutionary polynomial regression(EPR)in predicting Cc is comprehensively investigated.A database with a total number of 311 datasets including three input variables,i.e.initial void ratio e0,liquid limit water content wL,plasticity index Ip,and one output variable Cc is first established.Genetic algorithm(GA)is used to optimize the hyper-parameters in five ML algorithms,and the average prediction error for the 10-fold cross-validation(CV)sets is set as thefitness function in the GA for enhancing the robustness of ML models.The results indicate that ML models outperform empirical prediction formulations with lower prediction error.RF yields the lowest error followed by BPNN,ELM,EPR and SVM.If the ranges of input variables in the database are large enough,BPNN and RF models are recommended to predict Cc.Furthermore,if the distribution of input variables is continuous,RF model is the best one.Otherwise,EPR model is recommended if the ranges of input variables are small.The predicted correlations between input and output variables using five ML models show great agreement with the physical explanation. 展开更多
关键词 compressIBILITY Clays Machine learning Optimization Random forest Genetic algorithm
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