A network of the feedforward-type artificial neural networks (ANNs) was used to predict the compressive strength of concrete made from crude oil contaminated soil samples at 3, 7, 14, 28, 56, 84, and 168 days at different degrees of contamination of 2.5%, 5%, 10%, 15%, 20% and 25%. A total of 49 samples were used in the training, testing, and prediction phase of the modeling in the ratio 32？:？11？:？7. The TANH activation function was used and the maximum number of iterations was limited to 20,000 the model used a momentum of 0.6 and a learning rate of 0.031056. Twenty (20) different architectures were considered and the most suitable one was the 2-2-1. Statistical analysis of the output of the network was carried out and the correlation coefficient of the training and testing data is 0.9955712 and 0.980097. The result of the network has shown that the use of neural networks is effective in the prediction of the compressive strength of concrete made from crude oil impacted sand. 1. Introduction Concrete is unarguably the commonest material used in the construction of civil engineering structures; it is a mixture of cement, aggregates (fine and coarse), and water. The slurry (i.e., the cement and water) binds the aggregates to a hard mass; the paste hardens because of the hydration (i.e., the chemical reaction of the cement and water). It is a versatile construction material adaptable for different uses. Depending on the requirements demanded by the engineer, several other materials like admixture and additives can be added to alter the properties of the concrete in order to yield the expected result. The increase in demand for crude oil as a source of energy and as a primary raw material for industries has resulted in an increase in its production, transportation, and refining which in turn has resulted in gross pollution of the environment. Oil pollution occurs when crude oil is introduced into the environment directly or indirectly by man’s activities resulting in an unfavourable change in such a way that the safety and welfare of any living organism are endangered. The principal causes of oil pollution in the world include poor designs of ships and terminals, mechanical failure, operation procedures, human error, oil well blowout, and transportation. Other causes of oil spillage in Nigeria arise from corrosion of pipelines and tankers and sabotage [1]. Due to this occurrence of spillage, the sand of the environment gets contaminated with crude oil. It is this contaminated sand that is used in the making of concrete to erect structures in the
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