Optimizing cropping pattern to improve the performance of irrigation network using system dynamics-Powell algorithm.

One of the strategies for agricultural development is the optimal use of irrigation and drainage networks, which leads to higher productivity and economic benefits. In this regard, quantitative and qualitative studies of drainage water from networks are essential for efficient water management. In the present study, we develop a model using a system dynamics approach to simulate the cropping pattern of an irrigation and drainage network as well as the discharge and salinity of drainage water from network farms.

Analysis of the Challenges of Artificial Intelligence of Things (AIoT) for the Smart Supply Chain (Case Study: FMCG Industries).

In today's competitive world, supply chain management is one of the fundamental issues facing businesses that affects all an organization's activities to produce products and provide services needed by customers. The technological revolution in supply chain logistics is experiencing a significant wave of new innovations and challenges. Despite the current fast digital technologies, customers expect the ordering and delivery process to be faster, and as a result, this has made it easier and more efficient for organizations looking to implement new technologies.

Evaluation of geostatistical techniques and their hybrid in modelling of groundwater quality index in the Marand Plain in Iran.

In many parts of the world, groundwater is considered as one of the main sources of urban and rural drinking water. Over the past three decades, the qualitative and quantitative characteristics of aquifers have been negatively affected by different factors such as excessive use of chemical fertilizers in agriculture, indiscreet, and over-exploitation use of groundwater. Therefore, finding the effective method for mapping the water quality index (WQI) is important for locating suitable and non-suitable areas for urban and rural drinking waters.