M. S. S. Khan

Learn More
— this paper presents the bio-inspired neuro-fuzzy based route selection system to avoid traffic congestion. The proposed neuro-fuzzy system selects the best multi-parameters direction between two desired nodes: source and the endpoint. This research practices a mixture of neuro-fuzzy logic and ant colony system (ACS) algorithm for the principal routing to(More)
— This research paper describes the design and implementation of an autonomous room air cooler using fuzzy rule based control system. The rule base receives two crisp input values from temperature and humidity sensors, divides the universe of discourse into regions with each region containing two fuzzy variables, fires the rules, and gives the output(More)
— This research work presents an application of fuzzy logic for multi-agent based autonomous traffic lights control system using wireless sensors to overcome problems like congestion, accidents, speed and traffic irregularity. The proposed agent based approach can provide a preferred solution by minimizing the vehicle waiting time especially the emergency(More)
The SIR model is used extensively in the field of epidemiology, in particular, for the analysis of communal diseases. One problem with SIR and other existing models is that they are tailored to random or Erdos type networks since they do not consider the varying probabilities of infection or immunity per node. In this paper, we present the application and(More)
— This paper presents the speed scheduling system of autonomous railway vehicles using neuro-fuzzy system. Speed maintaining and scheduling system is considered integral part for successful development of autonomous railway vehicle control system. This work focuses on development of intelligent speed scheduling system to successfully cope with constraint of(More)
— this paper presents the approach of neuro fuzzy systems to design autonomous vehicle control system. The purposed intelligent controller deliberates obstacles avoidance, unstructured environment adaptation and speed scheduling of autonom ous vehicle based on neuro-fuzzy with reinforcement learning mechanism. The purposed system provides the autonomous(More)
—This paper presents the design model of speed scheduling system of autonomous railway vehicle control using fuzzy inference system (FIS). Successful development of speed scheduling and maintaining system plays crucial role to make autonomous railway vehicle control system more effective under constraint of uncertain conditions. This research work emphasis(More)
—This research work presents an autonomous system for premises environment control using fuzzy logic. This proposed design of control system has four inputs: luminance intensity, luminance mode, temperature and humidity. There are six controlling outputs for luminance controller, air conditioner, ceiling fan, air-cooler fan, water-pump and heating unit.(More)