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In the last few decades, with the development of computers and geographic information system (GIS), a wide range of landslide susceptibility zonation (LSZ) techniques were orchestrated by various researchers around the globe. Among them, the artificial intelligence (AI) have been distinctly regarded as the most effective and suitable approach to part with GIS for LSZ. Though, suitability of AI for...
A landslide susceptibility map (LSM) is an imperative element in the planning of sustainable development practices and geo-environmental conservations in mountainous terrains. In recent times, approaches that couple soft computing techniques and Geographic Information System (GIS) has emerged as better-suited models that can diminish the flaws and limitations of heuristic, probabilistic and distribution...
Evolutionary fuzzy extreme learning machine (EF-ELM) is one of the neuro-fuzzy system, which combines the learning capabilities of extreme learning machine (ELM) and the explicit knowledge of the fuzzy systems. In EF-ELM, the differential evolutionary technique is used to tune the membership function parameters were as the consequent parameters are tuned by Moore-Penrose generalized inverse techniques...
In the field of robotics, the two wheel mobile manipulator has the potential to perform wide range of applications. Balancing of the system becomes a bothering task due to the highly unstable nature of the system. Dynamics of wheeled mobile manipulator are derived by the basics of energy balance equation by approximating double inverted pendulum dynamics. Control method for balancing the two wheeled...
This paper deals with dynamic modeling and tip position control of flexible beam manipulator with flexible joint while suppressing the link vibrations. The nonlinear dynamic model of the flexible beam manipulators has been derived using the idea of Lagrangian mechanics and assumed modes method (AMM). A complete model has derived with damping and friction effects in addition to rotor inertia and joint...
Extreme Learning Adaptive Neuro Fuzzy Inference System (ELANFIS) is a new learning machine which combines the learning capabilities of neural networks and the explicit knowledge of the fuzzy systems as in the case of conventional adaptive neuro-fuzzy inference system (ANFIS). ELANFIS reduces the computational complexity of ANFIS by eliminating the hybrid learning algorithm and avoids the randomness...
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