A new technique is proposed, called Double Group bs, for consistent estimation of the number and locations of multiple change-points in data. It is an improvement of bs algorithm. There are two main contributions as f...
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A new technique is proposed, called Double Group bs, for consistent estimation of the number and locations of multiple change-points in data. It is an improvement of bs algorithm. There are two main contributions as follows. Firstly, data is cut into some segments, so the proposed algorithm is faster than bs. Secondary, the double procedure give a more stable recognition for change-points. The method is evaluated by simulation.
Sensor placement optimisation is an important problem in the field of structural health monitoring (SHM). Many researchers solve this problem by focusing only on the network requirements, without considering the civil...
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Sensor placement optimisation is an important problem in the field of structural health monitoring (SHM). Many researchers solve this problem by focusing only on the network requirements, without considering the civil engineering requirements. However, there are researchers that optimise the sensor placement considering network and civil requirements. Unfortunately, those researchers did not address minimising the number of sensors. As a result, in this research we study the problem of minimising the number of sensors for SHM in wireless sensors networks satisfying both civil and network requirements. The authors' contribution in this work is showing the mathematical model of the mentioned problem. Then, solve the problem using different methods: exhaustive search, genetic algorithm (GA), and a numerical iterative algorithm that applies binary search (bs). The problem is solved using different number of sensors as well as different placements in many conducted experiments. The obtained results showed that minimising the number of sensors becomes more significant with big structures. Furthermore, the bs algorithm is the best to use to solve the problem for small buildings. However, for larger buildings, there is a trade-off between the performance, and time complexity, where the bs gives optimal solution, but GA gives better time execution.
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