This Perspective discusses the limitations of current grid data prediction technologies and emphasizes the need for more reliable, interpretable, and data-driven approaches to support the increasing complexity of modern power systems and the ongoing energy transition. More >

As the field of computational optimization and reasoning accelerates toward new frontiers, it is vital that our research community remains aware of the emerging trends reshaping this dynamic landscape. At the Journal of Computational Optimization and Reasoning (JCOR), we are committed to being at the forefront of these developments—curating and disseminating impactful work that not only advances theory but also addresses the complex challenges of our time. More >

Agriculture plays a major role in India’s growth. Timely prediction of diseases will minimize their impact and improve productivity in agriculture. This work focuses on designing a rover-based system for automated plant disease detection. The rover can be utilized to detect plants without human intervention. The COCO/SSD model is used for object detection. After detecting the plant, the motor is actuated to move the rover near it. The “Plant Village” dataset is used to train the model. It consists of various images of healthy and diseased plants. In this project, we have used tomato, potato, corn, and grape images to train the model for disease identification. We have used various deep... More >

We welcome you to the inaugural issue of the Journal of Computational Optimization and Reasoning. This journal has been established to serve as a leading platform for researchers, practitioners, and innovators dedicated to the study and advancement of computational optimization techniques, reasoning methodologies, and their transformative applications across diverse domains. More >