期刊文献+
任意字段
题名或关键词
题名
关键词
摘要
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息
共找到50篇文章
< 1 2 3 >
每页显示 20 50 100
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
显示方式：
Research on Modeling of Genetic Networks Based on Information Measurement 认领 引用
1
作者 张国伟 邵世煌 +1 位作者 张颖 李海鹰 《Journal of Shanghai Jiaotong university(Science)》 EI 2006年第2期259-262,共4页
As the basis of network of biology organism, the genetic network is concerned by many researchers. Current modeling methods to genetic network, especially the Boolean networks modeling method are analyzed. For modelin... As the basis of network of biology organism, the genetic network is concerned by many researchers. Current modeling methods to genetic network, especially the Boolean networks modeling method are analyzed. For modeling the genetic network, the information theory is proposed to mining the relations between elements in network. Through calculating the values of information entropy and mutual entropy in a case, the effectiveness of the method is verified. 展开更多
关键词 genetic networks mutual information modeling
暂未订购 下载PDF
Computing a Predictor Set Influence Zone through a Multi-Layer Genetic Network to Explore the Role of Estrogen in Breast Cancer 认领 引用
2
作者 Leandro de ALima Marcelo Ris +2 位作者 Junior Barrera Maria M.Brentani Helena Brentani 《Advances in Breast Cancer Research》 CAS 2012年第3期21-29,共9页
Modeling inter-relationships of genes over a specific genetic network is one of the most challenging studies in systems biology. Among the families of models proposed one commonly used is the discrete stochastic, base... Modeling inter-relationships of genes over a specific genetic network is one of the most challenging studies in systems biology. Among the families of models proposed one commonly used is the discrete stochastic, based on conditionally independent Markov chains. In practice, this model is estimated from time sequential sampling, usually obtained by microarray experiments. In order to improve the accuracy of the estimation method, we can use biological knowledge. In this paper, we decided to apply this idea to study the role of estrogen in breast cancer proliferation. The n-influence zone of a set S of genes in a given multi-layer genetic network is a set L of genes regulated, directly or indirectly, by genes in S, after at most n-1 layers. In this manuscript we describe a new approach for computing the n-influence zone of S through the estimation of a multi-layer genetic network from gene expression time series, measured by microarrays, and biological knowledge. Using seed genes related to cell proliferation, our method was able to add to the third layer of the network other genes related to this biological function and validated in the literature. Using a set of genes directly influenced by estrogen, we could find a new role for cell adhesion genes estrogen dependent. Our pipeline is user-friendly and does not have high system requirements. We believe this paper could contribute to improve the data mining for biologists in microarray time series. 展开更多
关键词 Genetic Regulatory Networks Estrogen Time-Course Microarrays
暂未订购 下载PDF
Genetic interaction network of quantitative trait genes for heading date in rice 认领 引用 被引量：1
3
作者 Mengjiao Chen Yifeng Hong +6 位作者 Jiongjiong Fan Dengyi Cao Chong Yin Anjie Yu Jie Qiu Xuehui Huang Xin Wei 《Journal of Genetics and Genomics》 SCIE CAS CSCD 2025年第6期747-760,共14页
Several quantitative trait genes(QTGs)related to rice heading date,a key factor for crop development and yield,have been identified,along with complex interactions among genes.However,a comprehensive genetic interacti... Several quantitative trait genes(QTGs)related to rice heading date,a key factor for crop development and yield,have been identified,along with complex interactions among genes.However,a comprehensive genetic interaction network for these QTGs has not yet been established.In this study,we use 18K-rice lines to identify QTGs and their epistatic interactions affecting rice heading date.We identify 264 pairs of interacting quantitative trait loci(QTL)and construct a comprehensive genetic network of these QTL.On average,the epistatic effects of QTL pairs are estimated to be approximately 12.5%of additive effects of identified QTL.Importantly,epistasis varies among different alleles of several heading date genes.Additionally,57 pairs of interacting QTGs are also significant in their epistatic effects on 12 other agronomic traits.The identified QTL genetic interactions are further validated using near-isogenic lines,yeast two-hybrid,and split-luciferase complementation assays.Overall,this study provides a genetic network of rice heading date genes,which plays a crucial role in regulating rice heading date and influencing multiple related agronomic traits.This network serves as a foundation for understanding the genetic mechanisms of rice quantitative traits and for advancing rice molecular breeding. 展开更多
关键词 Genetic network Epistasis Epistatic effect Quantitative trait gene Rice Heading date
暂未订购 下载PDF
Dissecting the genetic basis of agronomic traits by multi-trait GWAS and genetic networks in maize(Zea mays L.) 认领 引用
4
作者 Ying Zhou Yanfang Heng +10 位作者 Shoukun Chen Jinglu Wang Kunhui He Jiahui Geng Kaijian Fan Yonggui Xiao Changling Huang Jiankang Wang Enying Zhang Liang Li Huihui Li 《aBIOTECH》 EI CAS CSCD 2025年第4期707-725,共19页
Agronomic traits in maize(Zea mays L.)are complex and modulated by pleiotropic loci and interconnected genetic networks.However,the traditional single-trait genome-wide association study(GWAS)method often misses genet... Agronomic traits in maize(Zea mays L.)are complex and modulated by pleiotropic loci and interconnected genetic networks.However,the traditional single-trait genome-wide association study(GWAS)method often misses genetic associations among traits,overlooks pleiotropic effects,and underestimates shared regulatory mechanisms.In the current study,we employed multi-trait analysis of GWAS(MTAG)and constructed a genetic network to dissect the genetic architecture of 18 agronomic traits across a genetically diverse panel of 2,448 maize inbred lines.Incorporating MTAG significantly improved the detection of pleiotropic loci that had not been detected by single-trait GWAS.Using a genetic network,we uncovered numerous previously unrecognized connections among traits related to plant architecture,yield,and flowering time.The 49 detected hub nodes,including Zm00001d028840 and Zm00001d033859(knotted1),influence multiple traits.Co-expression analysis of candidate genes across two developmental stages validated their distinct yet complementary roles,with Zm00001d028840 linked to early cell wall remodeling and Zm00001d033849 involved in chromatin remodeling during tasseling.Moreover,we integrated results from GWAS,MTAG,and genetic network analyses to prioritize pleiotropic loci and hub genes that regulate multiple agronomic traits.This integrative approach offers a practical framework for selecting stable,multi-trait-associated targets,thereby supporting more precise and efficient crop improvement strategies. 展开更多
关键词 Maize(Zea mays L.) Multi-trait GWAS Genes Genetic network
Stochastic Noise in Auto-regulatory Genetic Network:Model-dependence and Statistical Complication 认领 引用
5
作者 Ying-zi Shang 《Acta Mathematicae Applicatae Sinica》 SCIE 2008年第4期563-572,共10页
For the single gene network model, there are two basic types. For convenience, we call them Type I and Type II, respectively. The Type I model describes both the dynamics of mRNA and protein. The Type II model is a si... For the single gene network model, there are two basic types. For convenience, we call them Type I and Type II, respectively. The Type I model describes both the dynamics of mRNA and protein. The Type II model is a simplification of the Type I model based on the assumption that the change rate of mRNA is much faster than protein because the half-life of mRNA is short compared with that of protein, the Type II model describes only the dynamics of protein. The analysis of the Type I model is based on the assumption that the ratio of the protein decay rate to the mRNA decay rate is small enough. The main results for Type I model show that the Fano factor of the protein must be bigger than one if there is no negative feedback on the transcription. If there is negative feedback, the relative fluctuation strength in the number of proteins is determined by the size of the feedback regulation strength. For the Type II model, the Fano factor of the protein depends on the effect of the feedback regulation on the translation, i.e., the Fano factor equals one if there is no feedback, and is less than one （or bigger than one） if there is negative feedback （or positive feedback）. These results show clearly that the analysis of the steady-state statistical properties of single gene network is model-dependent. 展开更多
关键词 Genetic network model-dependence fano factor intrinsic noise
暂未订购 下载PDF
Oscillatory and anti-oscillatory motifs in genetic regulatory networks 认领 引用 被引量：1
6
作者 叶纬明 张朝阳 +2 位作者 吕彬彬 狄增如 胡岗 《Chinese Physics B》 SCIE EI CAS CSCD 2012年第6期10-18,共9页
Recently, self-sustained oscillatory genetic regulatory networks （GRNs） have attracted significant attention in the biological field. Given a GRN, it is important to anticipate whether the network could generate osc... Recently, self-sustained oscillatory genetic regulatory networks （GRNs） have attracted significant attention in the biological field. Given a GRN, it is important to anticipate whether the network could generate oscillation with proper parameters, and what the key ingredients for the oscillation are. In this paper the ranges of some function-related parameters which are favorable to sustained oscillations are considered. In particular, some oscillatory motifs appearing with high-frequency in most of the oscillatory GRNs are observed. Moreover, there are some anti-oscillatory motifs which have a strong oscillation repressing effect. Some conclusions analyzing these motif effects and constructing oscillatory GRNs are provided. 展开更多
关键词 genetic regulatory network, oscillatory motif anti-oscillatory motif feedback loop
暂未订购 下载PDF
Stability of piecewise-linear models of genetic regulatory networks 认领 引用 被引量：1
7
作者 林鹏 秦开宇 吴海燕 《Chinese Physics B》 SCIE EI CAS CSCD 2011年第10期496-505,共10页
This paper investigates the stability of the equilibria of the piecewise-linear models of genetic regulatory networks on the intersection of the thresholds of all variables. It first studies circling trajectories and ... This paper investigates the stability of the equilibria of the piecewise-linear models of genetic regulatory networks on the intersection of the thresholds of all variables. It first studies circling trajectories and derives some stability conditions by quantitative analysis in the state transition graph. Then it proposes a common Lyapunov function for convergence analysis of the piecewise-linear models and gives a simple sign condition. All the obtained conditions are only related to the constant terms on the right-hand side of the differential equation after bringing the equilibrium to zero. 展开更多
关键词 genetic regulatory networks piecewise-linear model Lyapunov function
暂未订购 下载PDF
Numeral eddy current sensor modelling based on genetic neural network 认领 引用 被引量：8
8
作者 俞阿龙 《Chinese Physics B》 SCIE EI CAS 2008年第3期878-882,共5页
This paper presents a method used to the numeral eddy current sensor modelling based on the genetic neural network to settle its nonlinear problem. The principle and algorithms of genetic neural network are introduced... This paper presents a method used to the numeral eddy current sensor modelling based on the genetic neural network to settle its nonlinear problem. The principle and algorithms of genetic neural network are introduced. In this method, the nonlinear model parameters of the numeral eddy current sensor are optimized by genetic neural network （GNN） according to measurement data. So the method remains both the global searching ability of genetic algorithm and the good local searching ability of neural network. The nonlinear model has the advantages of strong robustness, on-line modelling and high precision. The maximum nonlinearity error can be reduced to 0.037% by using GNN. However, the maximum nonlinearity error is 0.075% using the least square method. 展开更多
关键词 modelling numeral eddy current sensor functional link neural network genetic neural network
暂未订购 下载PDF
Designing Genetic Regulatory Networks Using Fuzzy Petri Nets Approach 认领 引用 被引量：1
9
作者 Raed I.Hamed Syed I.Ahson Rafat Parveen 《International Journal of Automation and computing》 2010年第3期403-412,共10页
In this paper, we have successfully presented a fuzzy Petri net （FPN） model to design the genetic regulatory network. Based on the FPN model, an efficient algorithm is proposed to automatically reason about imprecis... In this paper, we have successfully presented a fuzzy Petri net （FPN） model to design the genetic regulatory network. Based on the FPN model, an efficient algorithm is proposed to automatically reason about imprecise and fuzzy information. By using the reasoning algorithm for the FPN, we present an alternative approach that is more promising than the fuzzy logic. The proposed FPN approach offers more flexible reasoning capability because it is able to obtain results with fuzzy intervals rather than point values. In this paper, a novel model with a new concept of hidden fuzzy transition （HFT） to design the genetic regulatory network is developed. We have built the FPN model and classified the input data in terms of time point and obtained the output data, so the system can be viewed as the two-input and one output system. This method eliminates possible false predictions from the classical fuzzy model thereby allowing a wider search space for inferring regulatory relationship. The experimental results show the proposed approach is feasible and acceptable to design the genetic regulatory network and investigate the dynamical behaviors of gene network. 展开更多
关键词 Genetic regulatory networks fuzzy Petri net （FPN） fuzzy reasoning fuzzy transition modeling.
暂未订购 下载PDF
Dissection of genetic network underlying important agronomic traits accelerates modern breeding in soybean 认领 引用
10
《Science Foundation in China》 2017年第4期
With the support by the National Natural Science Foundation of China and the'Strategic Priority Research Program'of the Chinese Academy of Sciences,a collaborative study by the research groups led by Professor... With the support by the National Natural Science Foundation of China and the'Strategic Priority Research Program'of the Chinese Academy of Sciences,a collaborative study by the research groups led by Professors Tian Zhixi(田志喜),Wang Guodong(王国栋),and Zhu Baoge(朱保葛)from the 展开更多
关键词 Dissection of genetic network underlying important agronomic traits accelerates modern breeding in soybean
暂未订购 下载PDF
Dynamics of network motifs in genetic regulatory networks 认领 引用
11
作者 李莹 刘曾荣 张建宝 《Chinese Physics B》 CAS 2007年第9期2587-2594,共8页
Network motifs hold a very important status in genetic regulatory networks. This paper aims to analyse the dynamical property of the network motifs in genetic regulatory networks. The main result we obtained is that t... Network motifs hold a very important status in genetic regulatory networks. This paper aims to analyse the dynamical property of the network motifs in genetic regulatory networks. The main result we obtained is that the dynamical property of a single motif is very simple with only an asymptotically stable equilibrium point, but the combination of several motifs can make more complicated dynamical properties emerge such as limit cycles. The above-mentioned result shows that network motif is a stable substructure in genetic regulatory networks while their combinations make the genetic regulatory network more complicated. 展开更多
关键词 genetic regulatory network motif feedback loop
暂未订购 下载PDF
Fuzzy Optimization of an Elevator Mechanism Applying the Genetic Algorithm and Neural Networks 认领 引用 被引量：2
12
作者 XI Ping-yuan WANG Bing +1 位作者 SHENTU Liu-fang HU Heng-yin 《International Journal of Plant Engineering and Management》 EI 2005年第4期236-240,共5页
Considering the indefinite character of the value of design parameters and being satisfied with load-bearing capacity and stiffness, the fuzzy optimization mathematical model is set up to minimize the volume of tooth ... Considering the indefinite character of the value of design parameters and being satisfied with load-bearing capacity and stiffness, the fuzzy optimization mathematical model is set up to minimize the volume of tooth corona of a worm gear in an elevator mechanism. The method of second-class comprehensive evaluation was used based on the optimal level cut set, thus the optimal level value of every fuzzy constraint can be attained; the fuzzy optimization is transformed into the usual optimization. The Fast Back Propagation of the neural networks algorithm are adopted to train feed-forward networks so as to fit a relative coefficient. Then the fitness function with penalty terms is built by a penalty strategy, a neural networks program is recalled, and solver functions of the Genetic Algorithm Toolbox of Matlab software are adopted to solve the optimization model. 展开更多
关键词 elevator mechanism fuzzy design optimization genetic algorithm and neural networks toolbox
暂未订购 下载PDF
Focusing light through turbid and thick scattering media via a hybrid genetic neural network algorithm 认领 引用
13
作者 YU LIU PENG SU +3 位作者 JIANHUA HUANG HUIFANG LIN PENGFEI WANG FENG HUANG 《Photonics Research》 SCIE EI CAS CSCD 2026年第5期2306-2316,共11页
Over the past decade,techniques for focusing scattered light through dynamic media have made considerable progress,which shows great potential for biomedical imaging,manipulation,and therapy.All of these techniques,ho... Over the past decade,techniques for focusing scattered light through dynamic media have made considerable progress,which shows great potential for biomedical imaging,manipulation,and therapy.All of these techniques,however,follow a default principle that the focusing speed must approach the speckle decorrelation time,which hinders applications in living tissues and deep scattering media.Here,we propose a novel perspective that random speckles contain a substantial amount of ballistic light undergoing high-order diffraction over an extended light path.This finding suggests a potential method for focusing light through turbid media,particularly in situations where only a small amount of scattered light can be detected,provided that the ballistic light can be efficiently separated. 展开更多
关键词 turbid media focusing scattered light dynamic media living tissues hybrid genetic neural network speckle decorrelation time biomedical imagingmanipulationand scattering media ballistic light
暂未订购 下载PDF
A New Modeling Method Based on Genetic Neural Network for Numeral Eddy Current Sensor 认领 引用
14
作者 Along Yu Zheng Li 《稀有金属材料与工程》 SCIE EI CAS 北大核心 2006年第A3期611-613,共3页
In this paper,we present a method used to the numeral eddy current sensor modeling based on genetic neural network to settle its nonlinear problem.The principle and algorithms of genetic neural network are introduced.... In this paper,we present a method used to the numeral eddy current sensor modeling based on genetic neural network to settle its nonlinear problem.The principle and algorithms of genetic neural network are introduced.In this method, the nonlinear model parameters of the numeral eddy current sensor are optimized by genetic neural network (GNN) according to measurement data.So the method remains both the global searching ability of genetic algorithm and the good local searching ability of neural network.The nonlinear model has the advantages of strong robustness,on-line scaling and high precision.The maximum nonlinearity error can be reduced to 0.037% using GNN.However,the maximum nonlinearity error is 0.075% using least square method (LMS). 展开更多
关键词 modeling eddy current sensor functional link neural network genetic algorithm genetic neural network
暂未订购 下载PDF
Dynamics and Mechanism of A Quorum Sensing Network Regulated by Small RNAs in Vibrio Harveyi 认领 引用 被引量：3
15
作者 SHEN Jian-Wei 《Communications in Theoretical Physics》 SCIE CAS CSCD 2011年第3期465-472,共8页
Bacterial quorum sensing （QS） has attracted much interests and it is an important process of cell communication. Recently, Bassler et al. studied the phenomena of QS regulated by small RNAs and the experimental data... Bacterial quorum sensing （QS） has attracted much interests and it is an important process of cell communication. Recently, Bassler et al. studied the phenomena of QS regulated by small RNAs and the experimental data showed that smafl RNAs played important role in the QS of Vibrio harveyi and it can permit the fine-tuning of gene regulation and mmntenance of homeostasis. According to Michaelis-Menten kinetics and mass action law in this paper, we construct a mathematical model to investigate the mechanism induced QS by coexist of small RNA and signal molecular （AI） and show that there are periodic oscillation when the time delay and Hill coefficient exceed a critical value and the periodic oscillation produces the change of concentration and induces QS. These results are fit to the experimental results. In the meanwhile, we also get some theoretical value of Hopf Bifurcation on time deday. In addition, we also find this network is robust against noise. 展开更多
关键词 quorum sensing genetic network oscillation small RNA bifurcation negative feedback loop
暂未订购 下载PDF
Nonlinear model predictive control based on support vector machine and genetic algorithm 认领 引用 被引量：16
16
作者 冯凯 卢建刚 陈金水 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2015年第12期2048-2052,共5页
This paper presents a nonlinear model predictive control(NMPC) approach based on support vector machine(SVM) and genetic algorithm(GA) for multiple-input multiple-output(MIMO) nonlinear systems.Individual SVM is used ... This paper presents a nonlinear model predictive control(NMPC) approach based on support vector machine(SVM) and genetic algorithm(GA) for multiple-input multiple-output(MIMO) nonlinear systems.Individual SVM is used to approximate each output of the controlled plant Then the model is used in MPC control scheme to predict the outputs of the controlled plant.The optimal control sequence is calculated using GA with elite preserve strategy.Simulation results of a typical MIMO nonlinear system show that this method has a good ability of set points tracking and disturbance rejection. 展开更多
关键词 Support vector machine Genetic algorithm Nonlinear model predictive control Neural network Modeling
暂未订购 下载PDF
Structure and Dynamics of Artificial Regulatory Networks Evolved by Segmental Duplication and Divergence Model 认领 引用 被引量：1
17
作者 Xiang-Hong Lin Tian-Wen Zhang 《International Journal of Automation and computing》 2010年第1期105-114,共10页
Based on a model of network encoding and dynamics called the artificial genome, we propose a segmental duplication and divergence model for evolving artificial regulatory networks. We find that this class of networks ... Based on a model of network encoding and dynamics called the artificial genome, we propose a segmental duplication and divergence model for evolving artificial regulatory networks. We find that this class of networks share structural properties with natural transcriptional regulatory networks. Specifically, these networks can display scale-free and small-world structures. We also find that these networks have a higher probability to operate in the ordered regimen, and a lower probability to operate in the chaotic regimen. That is, the dynamics of these networks is similar to that of natural networks. The results show that the structure and dynamics inherent in natural networks may be in part due to their method of generation rather than being exclusively shaped by subsequent evolution under natural selection. 展开更多
关键词 Genetic regulatory network （GRN） artificial regulatory network （ARN） segmental duplication and divergence scale-free small-world largest Lyapunov exponent.
暂未订购 下载PDF
Understanding biological functions through molecular networks 认领 引用 被引量：10
18
作者 Han,JD 《Cell Research》 SCIE CAS 2008年第2期224-237,共14页
The completion of genome sequences and subsequent high-throughput mapping of molecular networks have allowed us to study biology from the network perspective. Experimental, statistical and mathematical modeling approa... The completion of genome sequences and subsequent high-throughput mapping of molecular networks have allowed us to study biology from the network perspective. Experimental, statistical and mathematical modeling approaches have been employed to study the structure, function and dynamics of molecular networks, and begin to reveal important links of various network properties to the functions of the biological systems. In agreement with these functional links, evolutionary selection of a network is apparently based on the function, rather than directly on the structure of the network. Dynamic modularity is one of the prominent features of molecular networks. Taking advantage of such a feature may simplify network-based biological studies through construction of process-specific modular networks and provide functional and mechanistic insights linking genotypic variations to complex traits or diseases, which is likely to be a key approach in the next wave of understanding complex human diseases. With the development of ready-to-use network analysis and modeling tools the networks approaches will be infused into everyday biological research in the near future. 展开更多
关键词 network data integration modularity molecular function genetic variation
暂未订购 下载PDF
GA-BASED PID NEURAL NETWORK CONTROL FOR MAGNETIC BEARING SYSTEMS 认领 引用 被引量：2
19
作者 LI Guodong ZHANG Qingchun LIANG Yingchun 《Chinese Journal of Mechanical Engineering》 EI CAS 2007年第2期56-59,共4页
In order to overcome the system non-linearity and uncertainty inherent in magnetic bearing systems, a GA（genetic algnrithm）-based PID neural network controller is designed and trained tO emulate the operation of a c... In order to overcome the system non-linearity and uncertainty inherent in magnetic bearing systems, a GA（genetic algnrithm）-based PID neural network controller is designed and trained tO emulate the operation of a complete system （magnetic bearing, controller, and power amplifiers）. The feasibility of using a neural network to control nonlinear magnetic bearing systems with unknown dynamics is demonstrated. The key concept of the control scheme is to use GA to evaluate the candidate solutions （chromosomes）, increase the generalization ability of PID neural network and avoid suffering from the local minima problem in network learning due to the use of gradient descent learning method. The simulation results show that the proposed architecture provides well robust performance and better reinforcement learning capability in controlling magnetic bearing systems. 展开更多
关键词 Magnetic bearing Non-linearity PID neural network Genetic algorithm Local minima Robust performance
暂未订购 下载PDF
A weighted selection combining scheme for cooperative spectrum prediction in cognitive radio networks 认领 引用
20
作者 Li Xi Song Tiecheng +2 位作者 Zhang Yueyue Chen Guojun Hu Jing 《Journal of Southeast University(English Edition)》 EI CAS 2018年第3期281-287,共7页
A weighted selection combining （WSC） scheme is proposed to improve prediction accuracy for cooperative spectrum prediction in cognitive radio networks by exploiting spatial diversity. First, a genetic algorithm-base... A weighted selection combining （WSC） scheme is proposed to improve prediction accuracy for cooperative spectrum prediction in cognitive radio networks by exploiting spatial diversity. First, a genetic algorithm-based neural network （GANN） is designed to perform spectrum prediction in consideration of both the characteristics of the primary users （PU） and the effect of fading. Then, a fusion selection method based on the iterative self-organizing data analysis （ISODATA） algorithm is designed to select the best local predictors for combination. Additionally, a reliability-based weighted combination rule is proposed to make an accurate decision based on local prediction results considering the diversity of the predictors. Finally, a Gaussian approximation approach is employed to study the performance of the proposed WSC scheme, and the expressions of the global prediction precision and throughput enhancement are derived. Simulation results reveal that the proposed WSC scheme outperforms the other cooperative spectrum prediction schemes in terms of prediction accuracy, and can achieve significant throughput gain for cognitive radio networks. 展开更多
关键词 cognitive radio network cooperative spectrumprediction genetic algorithm-based neural network iterativeself-organizing data analysis algorithm weighted selectioncombining
暂未订购 下载PDF
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
上一页 1 2 3 下一页 到第 页
在线咨询 使用帮助 返回顶部 意见反馈