One can use nature as an optimizer efficiently. This paper presents different techniques for optimization using nature inspired algorithm. Though not all of them are efficient, a few algorithms have proved to be
Dhal KG, Ray S, Das A, Das S (2019) A survey on nature-inspired optimization algorithms and their application in image enhancement domain. Arch Comput Methods Eng 26(5):1607–1638 MathSciNet Google Scholar Dhiman G, Kumar V (2017) Spotted hyena optimizer: a novel bio-inspired based met...
Metaheuristic algorithms are generally nature-inspired and derivative-free. Hence, their implementation is not only considered to be simplistic, but also powerful in terms of convergence to the global optimum (Ezugwu et al., 2020). Their employment in data-driven modeling has exhibited positive ...
Optimization Algorithms introduces the AI algorithms that can solve these complex and poorly-structured problems. Inside you’ll find a wide range of optimization methods, from deterministic and stochastic derivative-free optimization to nature-inspired search algorithms and machine learning methods. Don’t...
and inter-cluster heterogeneity. This paper presents an up-to-date survey of major nature-inspired metaheuristic algorithms that have been employed to solve automatic clustering problems. Further, a comparative study of several modified well-known global metaheuristic algorithms is carried out to solve ...
What are fundamental structure of algorithms ? Sequential structure, selective structure and cycle structure. What is a process ? A set of instructions currently being processed by the computer processor. What is code review ? An activity to inspect and improve code quality by reading code. ...
Clever Algorithms: Nature-Inspired Programming Recipes Overview The Clever Algorithms project is an effort to describe a large number of algorithmic techniques from the the field of Artificial Intelligence in a complete, consistent, and centralized manner such that they are accessible, usable, and under...
In the next step, the ANFIS machine learning algorithm was used in combination with PSO and GWO meta-heuristic algorithms to train the data, and SWARA-ANFIS-PSO and SWARA-ANFIS-GWO susceptibility maps were separately generated for flood and landslide hazards. The predictive ability of the ...
Due to the black box nature of ML models, it is difficult to understand how they arrive at their conclusions, because these models are trained on massive amounts of data and employ complex algorithms that are difficult to interpret24. A wide range of techniques has been employed to develop ...
laika -> The goal of this repo is to research potential sources of satellite image data and to implement various algorithms for satellite image segmentation PEARL -> a human-in-the-loop AI tool to drastically reduce the time required to produce an accurate Land Use/Land Cover (LULC) map, ...