Ku Ruhana Ku-Mahamud

Web‐based support system for flood response operation in Malaysia

Purpose – The purpose of this paper is to present the utilization of a web-based support system for flood response operation in Malaysia. The system is intentionally designed to improve process and data management towards providing prompt and effective response to victims. nDesign/methodology/approach – The implementation of the research adopted the knowledge acquisition method for implementing expert systems in organizations. The methodology consists of four phases of activities which are planning for knowledge acquisition, knowledge extraction, knowledge analysis, and knowledge verification. nFindings – The findings include the architecture of the web-based support system for flood response operation which is presented in the form of conceptual and software models. The architecture of web-based support systems for flood response operation can assist the flood management related nagencies in managing and maintaining data related to floods. It also allows them to monitor the current situation of flood-related matters.Practical implications – Web-based support systems for flood response operation is expected to improve the overall aspect of flood response operation by providing electronic features which facilitate nthe flood response process and data management. In future, expert systems for flood response operations is one of the enhancements to the current architecture.Originality/value – This paper presents the architecture of a web-based support system for flood response operation in Malaysia. The proposed architecture is beneficial for the flood management related agencies in order to plan further improvements in the current procedure for flood response.

Revisiting the pheromone evaluation mechanism in the interacted multiple ant colonies optimization framework

Interacted Multiple Ant Colonies Optimization (IMACO) is a newly proposed framework. Pheromone evaluation mechanism is playing a central role in this framework. This paper describes the newly proposed IMACO framework and proposes a more effective pheromone evaluation mechanism. Computational tests show that the new pheromone evaluation mechanism can furthermore improve the IMACO performance. These tests also show the capability of IMACO to outperform other well known ant algorithms like ant colony system and max-min ant system.