Dear Researchers, I'm interesting in the application of PSO optimization in civil engineering, I ask for help in developing a predicting model for the project cost using that technique, if any one can help in this area?
You'll get bunch of papers on the same in ASCE DB on Particle swarm optimization. Please check. Much study is already been done using such algorithms for strength design, Cost and size optimization of reinforce concrete structural elements. Also in many civil engineering applications this algorithm is been used. PSO is one of the best algorithm in optimization technique. Kindly refer attached papers and links.
I used the PSO in the problem of TBM penetration rate prediction and I think you should do the following:
1-Get some data with known input-output features
2-Choose/Develop a model for predicting the project cost, you could use some machine learning models/methods like ANNs or SVMs.
3-Convert your problem to a optimization problem where the goal is to find the best parameters for the prediction model in order to minimize the prediction error on test data.
4-Use PSO to solve the minimization problem.
I think a good example would be the following paper:
Many thanks for your interest, I attach a set of data represent the properties of concrete mix and its constituents (column 1-11), and the last column (12) represent the compressive strength of each combination of data set.
can you help in providing a PSO code to predict the compressive strength of such data set., and how to use this code to predict compressive strength for an a data set with no output (new set).