计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2015年
16期
86-92,141
,共8页
人体姿态识别%传感网%加速度传感器%随机森林%蜜蜂交配优化
人體姿態識彆%傳感網%加速度傳感器%隨機森林%蜜蜂交配優化
인체자태식별%전감망%가속도전감기%수궤삼림%밀봉교배우화
human posture pattern%sensor network%acceleration sensor%random forest%honey-bee mating optimization
针对随机森林算法静态性、容易陷入局部最优等问题，提出了一种蜜蜂交配优化的随机森林算法，并将该算法应用于基于加速度传感器的人体姿态识别。设计了一套以三轴加速度传感器MMA7260与无线通信模块CC2430相结合的数据采集系统，采集了五种日常行为和一种异常行为；从加速度值中提取了近斜率、前后差、均值、均方根和信号幅值面积5类特征矢量；采用改进的随机森林算法训练行为模型和进行分类识别。实验结果表明：该算法能有效地识别六种行为，具有较高的分类预测准确率和行为识别率，且具有较强的稳定性、鲁棒性、全局寻优和抗噪声能力。
針對隨機森林算法靜態性、容易陷入跼部最優等問題，提齣瞭一種蜜蜂交配優化的隨機森林算法，併將該算法應用于基于加速度傳感器的人體姿態識彆。設計瞭一套以三軸加速度傳感器MMA7260與無線通信模塊CC2430相結閤的數據採集繫統，採集瞭五種日常行為和一種異常行為；從加速度值中提取瞭近斜率、前後差、均值、均方根和信號幅值麵積5類特徵矢量；採用改進的隨機森林算法訓練行為模型和進行分類識彆。實驗結果錶明：該算法能有效地識彆六種行為，具有較高的分類預測準確率和行為識彆率，且具有較彊的穩定性、魯棒性、全跼尋優和抗譟聲能力。
침대수궤삼림산법정태성、용역함입국부최우등문제，제출료일충밀봉교배우화적수궤삼림산법，병장해산법응용우기우가속도전감기적인체자태식별。설계료일투이삼축가속도전감기MMA7260여무선통신모괴CC2430상결합적수거채집계통，채집료오충일상행위화일충이상행위；종가속도치중제취료근사솔、전후차、균치、균방근화신호폭치면적5류특정시량；채용개진적수궤삼림산법훈련행위모형화진행분류식별。실험결과표명：해산법능유효지식별륙충행위，구유교고적분류예측준학솔화행위식별솔，차구유교강적은정성、로봉성、전국심우화항조성능력。
Adapting to the problem on the static property and easy convergence to local optima of traditional random forest algorithm, a honey-bee mating optimization random forest algorithm is proposed, and it is used to recognize the human motion patterns that is based on an acceleration sensor. A data collect system that is consist of a 3D acceleration sensor MMA7260 and wireless communication module CC2430 is designed, and is used to collect five daily activity and one abnormal behavior. Then, five features(Approximation Slope, Front and Rear Subtract, mean, RMS and SMA)are extracted from the acceleration signal. Finally, the improved random forest algorithm is adopted as a classifier. The experimental results have confirmed that the proposed algorithm is effective to recognize the six activity, meanwhile, the algorithm has achieved high classification prediction accuracy and recognition rate, and it has stronger stabile, robustness, ability of global optimal and anti-noise.
