Table 3 Parameter setting of the algorithms.

From: Energy consumption prediction in buildings using LSTM and SVR modified by developed Henry gas solubility optimization

Algorithm

Parameter Setting

Equilibrium Optimizer (EO)

Population size: 50, Maximum iterations: 100, β (balance factor): 0.5, σ (mutation factor): 0.1

Dragonfly Algorithm (DA)

Number of individuals: 100, Maximum iterations: 200,

α (step size): 0.2, γ (attractiveness): 1.2

Whale Optimization Algorithm (WOA)

Population size: 50, Maximum iterations: 150,

A (emulation factor): 0.5, A_damp (damping factor): 0.8

Grey Wolf Optimizer (GWO)

Population size: 30, Maximum iterations: 100,

α (encircling coefficient): 2, β (wandering coefficient): 0.5

Moth-Flame Optimization Algorithm (MFO)

Number of moths: 50, Maximum iterations: 200, γ (light absorption coefficient): 0.2, σ (emission range): 0.1

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