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Workflow generation, resource management, and scheduling of workflow are three main components of grid based computing architecture. The components in traditional grid architecture require human intervention due to lack of intelligence and use of knowledge from historical data. We have identified the need of intelligence based automatic workflow generation, and the prediction on run-time of tasks for optimal allocation and reservation of resources. We propose soft computing based architecture of intelligent grid. We also propose the neural network based algorithmic flow for the resource matchmaking, the allocation and reservation, and the scheduling of workflow. Our proposed architecture and algorithmic flow does not require human intervention in workflow generation and in finding and allocating optimal resource for task execution. As our proposed work provides flexibility and reduces complexity in workflow generation, it saves the valuable time and cost of user.