摘要
随着经济的快速发展,市场经济的竞争也越发激烈。企业为了更好地适应经济的发展,必须要有强大的竞争力。通过订单与客户保持联系,能够准确了解客户的需求,为企业的生产提供充足的准备时间,有利于实现快速生产。通过选择自适应权重粒子群算法和BP神经网络相结合的方法,建立神经网络模型,训练数据,得到预测结果。并通过一个企业的订单实例,完成订单预测,从而验证算法的实用性。
The rapid development of economy leads to fierce competition in the market economy.ln order to better adapt to the development of society, the enterprise must have strong competitiveness. The enterprise keeps in touch with the customer through the order and accurate understanding about customer requirement, so it can provide enough time to prepare for the production and achieve rapid production. Through the use of adaptive inertia weight heavy partiele swarm algorithm and neural networks, model is built for completing prediction. And by the orders of an enterprise instance, the order foreeast is completed, so the practicality of the algorithm is verified.
出处
《机械工程师》
2013年第5期137-139,共3页
Mechanical Engineer
关键词
神经网络
粒子群算法
权值
阙值
neural networks
particle swarm algorithm
weights
threshold
