A hybridized artificial neural network and imperialist competitive algorithm optimization approach for prediction of soil compaction in soil bin facility

We were inspired to furnish information concerning the promising applicability of a hybrid approach involving artificial neural networks (ANNs), with manifold network functions, and a meta-heuristic optimization algorithm for prediction of soil compaction indices. The employed network functions were the prevailed feed-forward network and the novel cascade-forward network algorithms to accommodate multivariate inputs of wheel load, tire inflation pressure, number of passage, slippage, and velocity each at three different levels for estimating the study objectives of soil compaction (i.e. penetration resistance and soil sinkage). The experimentations were carried out in a soil bin facility utilizing a single wheel-tester. Each ANN trials was developed merely and then by merging with the recently introduced evolutionary optimization technique of imperialist competitive algorithm (ICA). The results were compared on the basis of a modified performance function (MSEREG) and coefficient of determination (R2). Our results elucidated that hybrid ICA–ANN further succeeded to denote lower modeling error amongst which, cascade-forward network optimized by ICA managed to yield the highest quality solutions.

[1]  Vicente Hernández,et al.  Combining Neural Networks and Genetic Algorithms to Predict and Reduce Diesel Engine Emissions , 2007, IEEE Transactions on Evolutionary Computation.

[2]  Kazım Çarman,et al.  Compaction characteristics of towed wheels on clay loam in a soil bin , 2002 .

[3]  A. A. Mahboubi,et al.  Comparing Neural Networks, Linear and Nonlinear Regression Techniques to Model Penetration Resistance , 2008 .

[4]  Daniel Graupe,et al.  Principles of Artificial Neural Networks , 2018, Advanced Series in Circuits and Systems.

[5]  Amin Shokrollahi,et al.  Evolving artificial neural network and imperialist competitive algorithm for prediction oil flow rate of the reservoir , 2013, Appl. Soft Comput..

[6]  Kazım Çarman,et al.  Prediction of soil compaction under pneumatic tires a using fuzzy logic approach , 2008 .

[7]  Siamak Talatahari,et al.  Optimum design of skeletal structures using imperialist competitive algorithm , 2010 .

[8]  Dirk Ansorge,et al.  The effect of tyres and a rubber track at high axle loads on soil compaction, Part 1 Single axle-studies , 2007 .

[9]  Johan Arvidsson,et al.  Soil stress as affected by wheel load and tyre inflation pressure , 2007 .

[10]  D. W. Reeves,et al.  IN-ROW SUBSOILING AND CONTROLLED TRAFFIC EFFECTS ON COASTAL PLAIN SOILS , 2007 .

[11]  Dirk Ansorge,et al.  The effect of tyres and a rubber track at high axle loads on soil compaction-Part 2: Multi-axle machine studies , 2008 .

[12]  Caro Lucas,et al.  Imperialist competitive algorithm: An algorithm for optimization inspired by imperialistic competition , 2007, 2007 IEEE Congress on Evolutionary Computation.

[13]  Indra Mani,et al.  Effect of multiple passes of tractor with varying normal load on subsoil compaction , 2011 .

[14]  Per Schjønning,et al.  Mechanical behaviour of an undisturbed soil subjected to loadings: Effects of load and contact area , 2007 .

[15]  Per Schjønning,et al.  Transmission of vertical stress in a real soil profile. Part II: Effect of tyre size, inflation pressure and wheel load , 2011 .