Advances in Continuous and Discrete Models

Theory and Modern Applications

Table 2 Execution time of test examples with different parameters

From: A novel improved extreme learning machine algorithm in solving ordinary differential equations by Legendre neural network methods

Example	m = 100			n = 10
Example	n = 5	n = 8	n = 10	m = 50	m = 200	m = 500
Example 1	0.0068	0.0073	0.0073	0.0073	0.0073	0.0077
Example 2	0.0057	0.0059	0.0065	0.0063	0.0063	0.0064
Example 3	0.0056	0.0059	0.0061	0.0060	0.0062	0.0068
Example 4	0.0037	0.0040	0.0040	0.0041	0.0042	0.0048
Example 5	0.0060	0.0063	0.0066	0.0063	0.0064	0.0071
Example 6	0.0056	0.0063	0.0062	0.0062	0.0061	0.0067
Example 7	0.0058	0.0059	0.0062	0.0060	0.0063	0.0067
Example 8	0.0057	0.0060	0.0061	0.0060	0.0062	0.0075
Example 9	0.0120	0.0121	0.0121	0.0122	0.0124	0.0132
Example 10	0.0118	0.0112	0.0114	0.0113	0.0117	0.0123
Example 11	0.0025	0.0030	0.0037	0.0033	0.0049	0.0082

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