An Empirical Estimation in Nuclear Hyperfine Spectroscopy: A Case Study of Measurements with TABU Search Algorithm
The recent advances in data analysis have been the emerging research problems in the scientific, engineering and technology etc. The learning algorithms have been deployed in extracting the information from available data set generated in scientific or engineering processes such as an expermentation. One of the potential optimal learning techniques is local search technique popularly known as Tabu which is implemented in the present work of processing the data of stochastic nature in the model experiment of hyperfine nuclear spectroscopy. There seems to no attempt in the execution of combinatorial metaheuristic iterative local seach algorithm in nuclear spectroscopy. The proposed technique of Tabu search algorithm is of significant nature of prohibiting the repeated visits of The Tabu solutions in the process of simulating the system. The feature of the algorithm is immediate local search so that it can forbidden the recitative solutions. The adjustment of various parameters that may explore the solution is clearly shown in the presentation. The interesting point to be noted in the attempt of Tabu search technique is that the sensitivity of measurements in the spectroscopy is enhanced 10 times other techniques implemented previously. The tabu search algorithm is to be a potential technique in processing of the data through the enhancement of signal to noise ratio.
Keywords - Tabu Search Algorithm, Combinatorial Metaheuristic Technique, Data Analysis, Spectroscopy