Global Journal of Computer Science and Technology, G: Interdisciplinary, Volume 23 Issue 1

Task nodes are rectangular in shape. Critical tasks are in red and non-critical are blue. Each task node provides the task name, start, finish, duration, resources, and ID. This is probably more information than we need and it makes distinguishing any task node information near impossible or difficult to read when the entire schedule network is displayed, as in Figure 8. Let’s simplify the node details using the Layout dialog, Figure 9. In the Layout dialog toggle on ‘Hide all fields except ID’. Now we can clearly see the entire schedule network and associated IDs, Figure 10. Fig. 10: Hide all fields except ID’ We also know that if we want more information on a network node we simply toggle off ‘Hide all fields except ID’. With only the ID displayed as in Figure 10 we can easily see the entire network in a way that provides useful insight. The node (task) predecessor and successor is apparent for each node. The critical path is clearly visible. We can also distinguish the nodes or tasks performed in parallel and/or series. Effective project management necessitates the utilization of business intelligence (BI) to evaluate project metrics. BI is employed to ascertain and validate decisions related to meeting needs and achieving project goals. During project initiation, funding considerations demand significant attention, while upon completion, the focus shifts to evaluating implementation effectiveness. Project indicators enable the assessment of individual management decisions and the overall project performance. Monitoring key performance indicators (KPIs) for the project is facilitated through a dashboard, an information panel displaying essential indicators through visualizations such as graphs, tables, and diagrams. The neural model comprises an external bias, which, depending on its positivity or negativity, augments or diminishes the network output upon activation of the activation function. Neuron K can be described using two equations, denoted as (1) and (2): = ∑ =1 (1) = ( + ) (2) The role of the threshold is to affine the output of the linear combiner within the model: = + (3) Bias represents an external parameter of artificial neuron K. The same relationship can be obtained by combining formula (2) and formula (3) as follows: = ∑ =0 (4) = ( ) (5) Where the activation function is represented by. (6) This represents the step function. The corresponding output in this scenario is given by: (7) Another activation function can be represented as. (8) Commonly used nonlinear functions are S function and radial basis function as shown in Figure 11. Data Visualization as a Means of Optimizing Control Systems Model in Project Management © 2023 Global Journals Global Journal of Computer Science and Technology Volume XXIII Issue I Version I 71 ( )G Year 2023