Algorithm membership function. by Mohamed Raef Smaoui (9865830)

“…<p>(Top) Input Membership Function. The algorithm classifies glucose input into 4 sets: low, medium, high, and ex_high. …”

Probability density of the cumulative number <i>C</i> of infections for different system sizes <i>N</i> at their critical vaccination doses with the random vaccination strategy as... by Yannick Feld (16520678)

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Cleavage time as a function of scaled fiber diameter. by Roukayatou R. Ouedraogo (20460980)

Results of proposed algorithms and algorithms in [9] for 18 instances. by Jin Zhang (53297)

Flowchart of the proposed algorithm. by Heewon Chung (2881286)

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P -values for SGHHO and other reported algorithms by Wilcoxon test on the benchmark function. by Qiong Wu (84327)

“…<p>P -values for SGHHO and other reported algorithms by Wilcoxon test on the benchmark function.…”

Multimodal reference functions. by Ruiyu Zhan (21602031)

“…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”

Infection time series <i>i</i>(<i>τ</i>) for different values of <i>C</i>. by Yannick Feld (16520678)

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Networking Chemicals Flows: Efficiency–Value–Environment Functionalized Symbiosis Algorithms and Application by Yizheng Lyu (17346506)

Networking Chemicals Flows: Efficiency–Value–Environment Functionalized Symbiosis Algorithms and Application by Yizheng Lyu (17346506)

Networking Chemicals Flows: Efficiency–Value–Environment Functionalized Symbiosis Algorithms and Application by Yizheng Lyu (17346506)

Rate functions Φ(<i>C</i>) for the random vaccination heuristics for different system sizes <i>N</i> at their respective critical vaccination. by Yannick Feld (16520678)

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APSO–CNN and FNN algorithms’ loss function training sets. by Ahmed Bahaa (12887063)

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APSO–CNN and FNN algorithms’ loss function validation sets. by Ahmed Bahaa (12887063)

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The convergence curves of the test functions. by Ruiyu Zhan (21602031)

“…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”

Single-peaked reference functions. by Ruiyu Zhan (21602031)

“…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”

Conditional density that shows the probability of for any given value of <i>C</i> for <i>N</i> = 3200 and <i>N</i>_<i>v</i> = 530 for the different vaccination strategies... by Yannick Feld (16520678)

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Test results of multimodal benchmark functions. by Ruiyu Zhan (21602031)

“…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”

Fixed-dimensional multimodal reference functions. by Ruiyu Zhan (21602031)

“…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”

Test results of multimodal benchmark functions. by Ruiyu Zhan (21602031)

“…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”