Abstract: This paper presents an alternative method for predicting biochar yields from biomass thermochem ical processes.The obtained results
were compared to those of other methods, such as ANFIS using gradient descent, practical swarm optimiza tion, genetic algorithm, whale optimization algorithm, sine-cosine algorithm, and LS-SVM.There fore, this paper avoids this limitation by using a hybrid method between the adaptive neuro-fuzzy inference
system (ANFIS) and gray wolf optimization (GWO) algorithm.The aim of the second experiment was to evaluate the performance of the pro posed ANFIS-GWO method to predict biochar yield from manure pyrolysis.Keywords: Gray wolf optimization (GWO), adaptive neuro-fuzzy inference system (ANFIS), renewable energy
production, biochar predictionSeveral methods have been presented to predict biochar, such as neural network (NN) and least
square support vector machine (LS-SVM).The proposed method is called ANFIS-GWO,
which consists of two stages.