求翻译：本设计先采用Sphere函数、Schwefel函数和Ackley函数对比说明了单机上的粒子群算法的特点。然后在十台Linux机的集群上搭建Hadoop平台，再利用MapReduce将粒子群算法改编，将其部署到HDFS上以实现其并行化，再次利用Sphere函数、Schwefel函数和Ackley函数，说明并行粒子群算法的特点。是什么意思？

The design of the first sphere function, schwefel function and ackley function, contrast describes the characteristics of the stand-alone on the particle swarm algorithm. Platform and then set up hadoop on a cluster of 10 Linux machines, and then use the mapreduce adaptation of particle swarm optimi

This design in a function, Schwefel Sphere Ackley function Function and compare notes on a single machine has the characteristics of particle cluster algorithm. And then in the 10 Linux Cluster built Hadoop MapReduce platform, and then use the particle cluster algorithm adapted to deploy it to HDFS

This design used the Sphere function, the Schwefel function and the Ackley function contrast first showed on the single plane grain of subgroup algorithm characteristic.Then builds the Hadoop platform on ten Linux machine colonies, again will use MapReduce the grain of subgroup algorithm reorganizat

The design Sphere functions, Schwefel and Ackley functions comparison illustrates the characteristics of Particle Swarm Optimization algorithm on a single machine. And then ten clusters of Linux machines built on Hadoop platform, then use MapReduce to particle swarm optimization algorithm for adapta

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