Critical analysis of Big Data challenges on similar sequential Algorithm based data Search

ABSTRACT For improvement of cycle method of force of china, there is need to organize and recuperate the prevalence of force source within the network, during this examination, as indicated by the non-intermittent and occasional qualities of the consistent public list of force greatness, an effect predominance consistent state list appraisal and conjecture framework established on turbulent plan hypothesis and littlest squares arrangement vector component in huge information foundation is planned. Initially, tumultuous framework hypothesis is used to remake the stage planetary of the authentic information of traditional force greatness consistent state files, and to make another information data space covering attractors. At that time, the LSSVM is employed to arrange the examples in high-dimensional space, and also the (PSO) calculation is used together to urge the simplest list assessment and expectation framework model. Simultaneously, the framework is applied to the important observing of the electrical energy treatment limit of a circulation network during a specific spot. The regular consistent state record of force quality is employed to assess and screen, and therefore the normal relative mistake is under 7%. Clearly, the end result is superior to the customary back spread (BP) neural organization forecast strategy, which demonstrates that the control class consistent state list assessment framework established on turbulent framework model and statistical procedure uphold course machine underneath enormous information may be broadly utilized.