5 research outputs found
Step Detection Algorithm For Accurate Distance Estimation Using Dynamic Step Length
In this paper, a new Smartphone sensor based algorithm is proposed to detect
accurate distance estimation. The algorithm consists of two phases, the first
phase is for detecting the peaks from the Smartphone accelerometer sensor. The
other one is for detecting the step length which varies from step to step. The
proposed algorithm is tested and implemented in real environment and it showed
promising results. Unlike the conventional approaches, the error of the
proposed algorithm is fixed and is not affected by the long distance.
Keywords distance estimation, peaks, step length, accelerometer.Comment: this paper contains of 5 pages and 6 figure
Improving TSP Solutions Using GA with a New Hybrid Mutation Based on Knowledge and Randomness
Genetic algorithm (GA) is an efficient tool for solving optimization problems by evolving solutions, as it mimics the Darwinian theory of natural evolution. The mutation operator is one of the key success factors in GA, as it is considered the exploration operator of GA. Various mutation operators exist to solve hard combinatorial problems such as the TSP. In this paper, we propose a hybrid mutation operator called "IRGIBNNM", this mutation is a combination of two existing mutations; a knowledgebased mutation, and a random-based mutation. We also improve the existing "select best mutation" strategy using the proposed mutation. We conducted several experiments on twelve benchmark Symmetric traveling salesman problem (STSP) instances. The results of our experiments show the efficiency of the proposed mutation, particularly when we use it with some other mutations