Table 11 Feature selection results on solar dataset using binary metaheuristics.

From: Optimizing solar and wind forecasting with iHow optimization algorithm and multi-scale attention networks

Optimizer

Avg. Error

Avg. Size

Avg. Fitness

Best Fitness

Worst Fitness

Std. Dev.

biHOW

0.4161

0.3689

0.4793

0.3811

0.4796

0.3016

bHHO

0.4339

0.5695

0.4961

0.4164

0.4833

0.3069

bGWO

0.4732

0.7028

0.5044

0.4579

0.5679

0.3251

bPSO

0.5667

0.6685

0.5935

0.5738

0.6415

0.4053

bWAO

0.5665

0.8319

0.6013

0.5654

0.6415

0.4075

bBBO

0.5349

0.8323

0.5992

0.5889

0.6754

0.4502

bMVO

0.5434

0.7650

0.6232

0.5484

0.6664

0.4560

bSFS

0.4363

0.5719

0.4985

0.4188

0.4857

0.3093

bSAO

0.4797

0.7113

0.5198

0.4095

0.5111

0.3186

bJAYA

0.4699

0.7353

0.5047

0.4688

0.5449

0.3109

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