Search Results - (( developing erp implementation algorithm ) OR ( java application optimisation algorithm ))

Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
Get full text
Get full text
Get full text

Efficient relay placement algorithm using landscape aware routing (erpalar) by Onabajo, Olawale Olusegun

“…Manual placement of wireless relay equipments will be a daunting task when deployment area spans over tens of kilometers and the environment made up of mountains, valleys and other terrains that could impact the transmission of radio-frequency Signal0 In this work, an algorithm code-named 'Efficient Relay Placement Algorithm using Landscape Aware Routing' -ERPALAR has been developed to solve the RPP. …”
Get full text
Get full text

Enhanced multi-agent approaches for efficient evacuation and rescue operations in managing disasters by Abusalama, Jawad

“…The research progresses through four stages: problem definition, approach design, implementation and evaluation, and simulation. For the evacuation phase, a Dynamic Real-Time Capacity Constrained Routing (DRTCCR) algorithm is introduced to address ERP challenges. …”
Get full text
Get full text

Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
Get full text
Get full text

Predictive analytics for pacemaker medical instrument stock management of Transmedic Healthcare by Nawawi, Nafiz Danial

“…This study focuses on pacemaker inventory management regarding inefficiencies in forecasts, resultant overstocking, and stockouts due to highly manual data entry at the front end and limited ERP visualisation capabilities. The research applies the CRISP-DM methodology, examining current stock processes, and then collecting and cleansing historical data to develop Always Better Control (ABC) for stock analysis and predictive models using classification and also making a comparison between three algorithms, which are Naive Bayes, Random Forest and Decision Tree. …”
Get full text
Get full text