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A simple flowchart representing a process for dealing with a non-functioning lamp. A flowchart is a type of diagram that represents a workflow or process. A flowchart can also be defined as a diagrammatic representation of an algorithm, a step-by-step approach to solving a task. The flowchart shows the steps as boxes of various kinds, and their ...
Nassi–Shneiderman diagrams are only rarely used for formal programming. Their abstraction level is close to structured program code and modifications require the whole diagram to be redrawn, but graphic editors removed that limitation. They clarify algorithms and high-level designs, which make them useful in teaching.
Power/Voltage-curve of a partially shaded PV system, with marked local and global MPP. Maximum power point tracking ( MPPT ), [ 1][ 2] or sometimes just power point tracking ( PPT ), [ 3][ 4] is a technique used with variable power sources to maximize energy extraction as conditions vary [ 5]. The technique is most commonly used with ...
Algorithm. In mathematics and computer science, an algorithm ( / ˈælɡərɪðəm / ⓘ) is a finite sequence of mathematically rigorous instructions, typically used to solve a class of specific problems or to perform a computation. [ 1] Algorithms are used as specifications for performing calculations and data processing.
The first structured method for documenting process flow, e.g., in flow shop scheduling, the flow process chart, was introduced by Frank and Lillian Gilbreth to members of ASME in 1921 as the presentation "Process Charts, First Steps in Finding the One Best Way to Do Work". [2] The Gilbreths' tools quickly found their way into industrial ...
Data-flow diagram. A data-flow diagram is a way of representing a flow of data through a process or a system (usually an information system ). The DFD also provides information about the outputs and inputs of each entity and the process itself. A data-flow diagram has no control flow — there are no decision rules and no loops.
v. t. e. Bootstrap aggregating, also called bagging (from b ootstrap agg regat ing ), is a machine learning ensemble meta-algorithm designed to improve the stability and accuracy of machine learning algorithms used in statistical classification and regression. It also reduces variance and helps to avoid overfitting.
Simulated annealing ( SA) is a probabilistic technique for approximating the global optimum of a given function. Specifically, it is a metaheuristic to approximate global optimization in a large search space for an optimization problem. For large numbers of local optima, SA can find the global optima. [ 1]
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