Table 1.

Hyper-parameters of proposed deep architecture

Subnets	Layer category	Hyper-parameters
		Activation function	Size	Filters	Dropout
Sequence	1D Convolution	Relu	2	201	0.4
		Relu	3	151	0.4
		Relu	5	101	0.4
	Dense	Relu	256	–	0.3
		Relu	128	–	0
		Sigmoid	2	–	–
Physico-O	Dense	Relu	256	–	0.2
		Relu	128	–	0.1
		Sigmoid	2	–	–
Physico-P	Dense	Relu	512	–	0.3
		Relu	256	–	0.2
		Relu	128	–	0.1
		Sigmoid	2	–	–
Physico-H	Dense	Relu	1024	–	0.4
		Relu	512	–	0.3
		Relu	256	–	0.2
		Relu	128	–	0.1
		Sigmoid	2	–	–
Physico-C	1D Convolution	Relu	2	201	0.2
		Relu	3	151	0.1
	Dense	Sigmoid	2	–	–
Physico-B	1D Convolution	Relu	2	201	0.3
		Relu	3	151	0.2
		Relu	5	101	0.1
	Dense	Sigmoid	2	–	–
Physico-A	1D Convolution	Relu	2	201	0.4
		Relu	3	151	0.3
		Relu	5	101	0.2
		Relu	7	51	0.1
	Dense	Sigmoid	2	–	–
Ensemble	Dense	Relu	7	–	–
		Sigmoid	2	–	–