Table 4.

Hybridization of SSA with deep learning algorithms

Refs	Models	Objective	Advantages	Disadvantages
[107]	SSA-BI-GRU	Bidirectional GRU (Bi-GRU) and time-series production forecasting approach based on the integration of (SSA)	Improve accuracy in data training	High iterations
			Reduce data training time
			Error reduction
[108]	LSTM-SSA	Short-term wind speed forecasting	Find the optimal value for network parameters	Problem of Overfitting with an increasing number of iterations
			Increase detection accuracy
			Improve accuracy in data training
			Increase detection accuracy
[109]	SCGRU-HSSA	Recognition of a linear source contamination	Improve accuracy in data training	Reduction of performance of middle neurons by increasing repetitions
			Settings for the number of layers and the number of nodes
[110]	SSA-CNN	COVID-19 diagnosis and categorization based on chest CT scans	Error reduction	Non-optimal updates of individual
				High execution time
[111]	VMD-ISSA-GRU	Short-Term Photovoltaic Power Forecasting	Increase detection accuracy	Reduction of performance of middle neurons by increasing repetitions
			Find the optimal value for network parameters
			Error reduction
			Improve the internal structure of the network
[112]	CEEMDAN-SSA-GRU	Wind power prediction	Find the optimal value for network parameters	Problem of Overfitting with an increasing number of iterations
			Reduce data training time
			Error reduction
[113]	BSSA-CNN	Optimal brain tumour diagnosis based on deep learning	Improve the internal structure of the network	High iterations
			Reduce data training time
[114]	IMEFD-ODCNN-SSA	Design fall detection systems for smart homecare	Error reduction	Reduce network speed in detecting samples
			Improve the internal structure of the network
[115]	TA-SSALSTM	Electric vehicle load forecast	Improve accuracy in data training	Reduce network speed in detecting samples
			Settings for the number of layers and the number of nodes
[116]	ESSA-CNN	Optimal brain tumour detection	Find the optimal value for network parameters	Reduction of performance of middle neurons by increasing repetitions
			Reduce data training time
			Error reduction
[117]	SWT-ISSA-LSTM	Water quality prediction	Error reduction	High execution time
			Improve the internal structure of the network
[118]	LSTM-SSSA	Accurate ultra-short-term wind speed prediction	Increase detection accuracy	Reduce network speed in detecting samples
			Find the optimal value for network parameters
			Error reduction
			Improve the internal structure of the network
[119]	SSA-LSTM	Residential high-power load prediction	Find the optimal value for network parameters	High execution time
			Reduce data training time
			Error reduction
[120]	ISSA-DELM	Accurate damage degree prediction	Find the optimal value for network parameters	High iterations
			Error reduction