基于改进遗传算法的电子商务交易风险评估

E-commerce transaction risk assessment based on improved genetic algorithm

为了降低电子商务交易的风险,需要进行交易风险的量化评估,提出一种基于改进遗传算法的电子商务交易风险评估方法。采用稀疏散点云数据采集技术进行电子商务交易信息的数据采样,并输入到云存储系统中建立电子商务交易风险数据评估的专家数据库,提取电子商务平台中商家的信任度推荐参量值,并进行信息融合处理。对融合后的商家信任度信息采用遗传算法进行交叉变异处理,结合自适应全局遗传进化方法实现电子商务交易风险信息的准确预测,从而实现交易风险评估。仿真结果表明,采用该方法进行电子商务交易风险评估的预测准确性较好,收敛误差较低,具有可行性。

In order to reduce the risk of e-commerce transaction,it is necessary to perform the quantitative evaluation of transaction risk,therefore an e-commerce transaction risk evaluation method based on improved genetic algorithm is put forward.The sparse scattered point cloud data technology is used to sample the data of the e-commerce transaction information,and input it into the cloud storage system. The specialist database of the e-commerce transaction risk data evaluation was established.The merchant trust recommendation parameters in e-commerce platform are extracted,and conducted with information fusion.The genetic algorithm is used to perform the crossover and mutation for the fused merchant trust information,and combined with the adaptive global genetic evolution algorithm to predict the e-commerce transaction risk information accurately,and realize the transaction risk assessment. The simulation results show that the method has high prediction accuracy and low convergence error for e-commerce transaction risk assessment,and is feasible.