Algorithm parameters can illustrate multiple instances of thought threads and function as mirror for thought processes. The multi-process algorithm can save costs, maximize profits, and deliver a competitive advantage for algorithm designer.
Multi-process algorithms have wide variety of features and parameter implementation base on system activities and desire-intentions or goals of profit maximization.
This study constraints algorithm features and describes two model-based approaches with pattern recognition. Multi process algorithms with parallel and consecutive based approaches can focus on structural patterns, general scenarios and embedded transaction processing on system platform.
Modeling multi-process algorithm with parallel approach modifies property of individual processes and entities on internal and external system environments through global variables at same time. This approach can contain two distinct phases. In the first phase, modified parameter property must establish in a roadmap of consolidation process. In second phase, a roadmap of consolidation process supposes to be aligned with instance threads of target. Parameter alignment set into array unique key in order to tackle target property. Outcome of multi-process algorithm planning is hidden profits according to (Fig 1) in the next section.
Multi-process algorithm with consecutive approach modifies property of individual processes and entities sequentially on internal and external system environments. Modified parameter property tackles target property. This approach may contain a range of multiple targets. Existence of multiple targets requires extra operation (Entanglement cycle) prior outcome of algorithm tackling according to (Fig 2) in the next section.
Feasible advantages of multi-process algorithm and complex task force operations are conditions for keeping integrity of system visions and keeping hidden benefits within various tactical operations.
Possible disadvantage for using multi-process algorithm is interception of transparent algorithm parameters by opponents (external forces).
Opponents can detect multi-process algorithm parameter implementation. Competitor may observe multi- process algorithm parameters and then identify instance of thought threads and real values on global variables. Evaluations of modified parameters on internal and external system environments illustrate desire-intentions or goal driven by algorithm designer.
Multi-process algorithm parameters can generate invisible entities on system platform.
Stimulus-response approach method can conduct for reliability of observation for entire process by opponents.