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| 1 | DDoS Attack Detection Scheme Based on Entropy and PSO-BP Neural Network in SDN显示文摘SDN (Software Defined Network) has many security problems, and DDoS attack is undoubtedly the most serious harm to SDN architecture network. How to accurately and effectively detect DDoS attacks has always been a difficult point and focus of SDN security research. Based on the characteristics of SDN, a DDoS attack detection method combining generalized entropy and PSOBP neural network is proposed. The traffic is pre-detected by the generalized entropy method deployed on the switch, and the detection result is divided into normal and abnormal. Locate the switch that issued the abnormal alarm. The controller uses the PSO-BP neural network to detect whether a DDoS attack occurs by further extracting the flow features of the abnormal switch. Experiments show that compared with other methods, the detection accurate rate is guaranteed while the CPU load of the controller is reduced, and the detection capability is better. | Zhenpeng Liu Yupeng He Wensheng Wang Bin Zhang | 2019 | China Communications2019，16，7： | 8 |
| 2 | 基于知识成熟度的动态正则化神经网络优化方法显示文摘传统的反向传播(BP)神经网络模型,在隐含层神经元较多时具有非常强大的表征能力,但同时也是因为这个原因,导致训练参数过多,难以避免造成过拟合现象,当训练数据非常有限时情况会更加严重。提出了一种基于知识成熟度的动态正则化神经网络优化方法 L2KM,不同于传统的L2正则化方法采用固定的先验假设,在模型训练的过程中根据学习到知识的成熟度动态地调整正则化参数,实现权值动态衰减。实验结果表明,这种动态正则化的神经网络优化方法能够有效地对抗过拟合,提升知识质量,提高模型的泛化能力。与传统的L2正则化方法相比,误分类率降低了42%左右。 | 邓青 程建军 王辉 邓林 | 2018 | 电子测量与仪器学报2018，32，2： | 3 |
| 3 | 基于结构MRI和机器学习的阿尔茨海默病病程分类研究显示文摘目的利用机器学习算法对阿尔茨海默病(Alzheimer’s disease,AD)病程进行分类,为临床早期诊断AD提供辅助工具。材料与方法将AD病程分为正常认知者、早期轻度认知障碍、晚期轻度认知障碍和AD 4组,收集这些研究对象的结构磁共振成像(structure magnetic resonance imaging,sMRI)数据,在此基础上加入年龄、性别、教育水平和简易智力状态检查(Mini-Mental State Examination,MMSE)评分,然后分别基于两个数据集用L1正则化支持向量机(L1 regularized support vector machine,L1-SVM)算法进行特征选择得到对分类组贡献最大的特征,将提取到的特征子集放入误差逆传播(back propagation,BP)神经网络模型中进行分类,并且与逻辑回归、随机森林、支持向量机3种机器学习模型作对比。用十折交叉验证法比较4种模型的准确率并给出最优组合模型的特异度、敏感度和AUC值。结果加入3项人口统计学指标和MMSE评分的特征集优于仅具有sMRI的特征集,此外,BP神经网络算法与L1-SVM特征选择算法结合的分类准确率优于其他机器学习模型,尤其是在从正常认知功能向AD转化的过程中,BP神经网络的准确率高达98.90%,敏感度98.75%,AUC值1.00。不同分类组之间略有差异。结论L1-SVM和BP神经网络组合模型可以用于AD早期诊断,并且AD进展转化的每一阶段的相关特征数据为临床基础研究和病理变化提供了依据。 | 姚丽丽 范炤 | 2021 | 磁共振成像2021，12，6： | 3 |
| 4 | 支持安全外包计算的无线体域网数据共享方案显示文摘如何有效保护无线体域网(WBAN)中数据共享时的数据安全是一个亟待解决的关键问题。传统的CP-ABE机制具有'一对多'的数据安全通信功能,适用于WBAN中的访问控制,但运算复杂度高且不支持属性撤销。充分考虑WBAN节点资源的有限性和用户属性的动态性,提出一种在标准模型下CPA安全、支持属性撤销、加密和解密安全外包计算的CP-ABE方案。与已有的方案相比,提出的方案在保证安全性的同时,终端的运算负担大为减少,且可以实时、细粒度地撤销用户属性。 | 张维纬 张育钊 黄焯 张茹 杨义先 | 2017 | 通信学报2017，38，4： | 3 |
| 5 | A BP neural network optimisation method based on dynamical regularization显示文摘When the traditional BP neural network has a big size of neurons in its hidden layers,it can own a very strong ability in fitting practical complex objective functions,but simultaneously for the same reason,the over-fitting problem is almost inevitable and will be more serious when there is only a very restricted size of training data.A new BP neural network optimisation method is given based on dynamical regularization(DRBP)in this paper.Differing from the traditional regularization method with an invariant prior assumption,this proposed method carries out weight decaying with adjusting regularization parameter dynamically according to the stability of the network during the whole training process.The results of experiments represented in this paper have shown that our method can antagonise the over-fitting problem effectively,reinforcing the generalisation ability of the model,and as an obvious result,the classification accuracy on the testing data is promoted. | Qing Deng | 2019 | Journal of Control and Decision2019，6，2： | 2 |
| 6 | 遗传算法结合反向传播算法神经网络优化党参多糖的提取工艺显示文摘目的通过遗传算法结合反向传播算法(back propagation,BP)神经网络,与正交实验结果对比,优化党参多糖的提取工艺。方法以党参多糖的提取率为指标,采用三因素(提取次数、提取时间、料液比)水平对BP神经网络模型参数进行优化,建立网络模型,并采用遗传算法对BP神经网络进行目标寻优,得到党参多糖的最佳提取工艺。结果得到的最优提取工艺为提取次数3次,提取时间2 h,料液比为1:10(m:m),在此条件下党参多糖得率预测值为55.29 mg/g,与实际测量值的相对误差仅为1.10%,具有较好的网络预测性。结论利用遗传算法结合BP神经网络对党参多糖的提取工艺进行优化具有较好的预测性,可以为党参的进一步研究开发提供新的思路。 | 张丽 田密 李凯 | 2020 | 食品安全质量检测学报2020，11，24： | 2 |
| 7 | 仿生嗅觉在空气净化器气味识别中的应用研究显示文摘随着人们对高水平生活的追求,家用空气净化器的使用已越来越普遍。将仿生嗅觉应用于空气净化器领域,并探究其可行性。根据常见的家居气味(一氧化碳、硫化氢、醛类、苯类和TVOC等有害气味)以及一些常见的异味,选择合适的传感器,组成传感器阵列进行气味数据采集。实验选择了香烟、香水、榴莲、油漆作为气味源,对采集后的数据使用PCA算法进行特征提取,并建立气味指纹信息库,使用MATLAB软件建立BP神经网络进行仿真模拟。实验结果表明,该方法对四类气味都有着较高的识别率,可见此识别方法具有可行性。 | 马东旭 骆德汉 徐勋庭 冯扬 钟平忠 方桦 | 2018 | 信息技术与网络安全2018，37，12： | 1 |
| 8 | Power Allocation for Energy Harvesting in Wireless Body Area Networks显示文摘Wireless Body Area Networks(WBANs) are expected to achieve high reliable communications among a large number of sensors.The outage probability can be used to measure the reliability of the WBAN.In this paper,we optimize the outage probability with the harvested energy as constraints.Firstly,the optimal transmit power of the sensor is obtained while considering a single link between an access point(AP) located on the waist and a sensor attached on the wrist over the Rayleigh fading channel.Secondly,an optimization problem is formed to minimize the outage probability.Finally,we convert the non-convex optimization problem into convex solved by the Lagrange multiplier method.Simulations show that the optimization problem is solvable.The outage probability is optimized by performing power allocation at the sensor.And our proposed algorithm achieves minimizing the outage probability when the sensor uses energy harvesting.We also demonstrate that the average outage probability is reduced with the increase of the harvested energy. | Xiaolan Liu Fengye Hu Meiqi Shao Dan Sui Gengxin He | 2017 | China Communications2017，14，6： | 1 |
| 9 | 行人交通参数提取算法改进与处理系统研发显示文摘为了解决行人交通参数获取困难、精度低等问题,需要开发出一套高精度、高效率和强抗干扰性的行人交通参数提取系统。首先,基于视频流中运动目标时空一致性的原理,采用运动目标梯度方向直方图(HOG)特征提取算法对视频流进行分割;其次,对运动目标特征进行分析并提取特征向量,建立反向传播(BP)神经网络对运动目标进行训练和分类,实现对运动目标的检测和识别;然后,利用MATLAB软件平台,开发了能够对行人流量、速度和时距等数据进行快速处理与准确分析的系统。最后,进行了实例测试。结果表明:检测系统的参数提取精度能达到90%以上,高于现有算法的提取精度。同时,系统有较强抗环境干扰性,提取效率和数据处理功能效果较理想。 | 罗强 吴淑博 臧晓冬 许伦辉 | 2018 | 科学技术与工程2018，18，9： | 0 |
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