en عمومى General پژوهشي Research <span lang="EN-US" style="font-size:10.0pt"><span style="line-height:150%"><span new="" roman="" style="font-family:" times=""><span style="color:black">Evaluating the energy efficiency of energy-efficient constructions relies heavily on accurately anticipating their thermal loads. Current results have demonstrated that stochastic algorithms effectively tackle the abovementioned problem. In light of these issues, this research aims to evaluate a novel hybrid technique for estimating dwellings&#39;</span></span></span></span><span lang="EN-US" style="font-size:10.0pt"><span style="line-height:150%"><span new="" roman="" style="font-family:" times=""><span style="color:black"> cooling load (CL). The multilayer perceptron and the Whale Optimization Algorithm (WOA-MLP) are both suggested components of the model. The nonlinear analysis of the impact of eight freestanding parameters on the cooling load was performed through the best structure of every model. The assessment for this investigation was carried out in two stages. During the first stage, the population size that </span></span></span></span><span lang="EN-US" style="font-size:11.0pt"><span style="background:white"><span style="line-height:150%"><span new="" roman="" style="font-family:" times=""><span style="color:black">yielded</span></span></span></span></span><span lang="EN-US" style="font-size:10.0pt"><span style="line-height:150%"><span new="" roman="" style="font-family:" times=""><span style="color:black"> the highest coefficient of determination (R²) value and the lowest root mean square error (RMSE) amount was selected as the optimal one. During the second stage, the experiment&rsquo; findings with a swarm size of 500 (R² =0.95155 and 0.95021, RMSE =0.07973 and 0.07737 for training and validation, correspondingly) were put through a series of tests using several various p values (between 0.5-1.4). According to the findings, the p-value of 1.3 is the one that provides the most reliable results. This amount has an R² equal to 0.95212 and 0.94792 and an RMSE equal to 0.07926 and 0.07909.</span></span></span></span> Residential buildings,Computational,Intelligence, WOA, Hybrid 37 60 http://aisesjournal.com/browse.php?a_code=A-10-360-1&slc_lang=en&sid=1 Gurpreet Singh Sokhal sokhal.guri@gmail.com 1003194753284600162 1003194753284600162 No Chandigarh University Gurprinder Singh Dhindsa gurpindere7284@cumail.in 1003194753284600163 1003194753284600163 No Chandigarh University Rupindder Singh rupinder_singh302@yahoo.com 1003194753284600164 1003194753284600164 Yes Chandigarh University Narinder Singh narinder.khattra126@gmail.com 1003194753284600165 1003194753284600165 No Chandigarh University Jugraj Singh Randhawa jrandhawa304@gmail.com 1003194753284600166 1003194753284600166 No Khalsa College of Engineering and Technology