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non-linear optimization solver fmincon  (MathWorks Inc)


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    MathWorks Inc non-linear optimization solver fmincon
    Trained Belief Rule Base Using <t> fmincon </t> for Patient Survival Probability (Y) where input antecedents are X1: Patient Condition, X2: Blood Pressure, X3: Chronic Obstructive Pulmonary Disease, X4: Blood Sugar, X5: Asthma, X6: Chronic Kidney Disease, X7: Obesity, X8: Acute Respiratory Distress Syndrome, X9: Pulse Oximetry, Critical: C, Non Critical: NC, Hypertensive Crisis: HC, Very Severely Abnormal: VSA, Diabetic: D, Severe Persistent: SP, Very Severe: VS, Level III: L-III, Severe: S, Moderate: M, Normal: N, Mild: Mi, VH: Very High, H: High, M: Medium, L: Low, VL: Very Low)
    Non Linear Optimization Solver Fmincon, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/non-linear optimization solver fmincon/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    non-linear optimization solver fmincon - by Bioz Stars, 2026-03
    90/100 stars

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    1) Product Images from "An Integrated Deep Learning and Belief Rule Base Intelligent System to Predict Survival of COVID-19 Patient under Uncertainty"

    Article Title: An Integrated Deep Learning and Belief Rule Base Intelligent System to Predict Survival of COVID-19 Patient under Uncertainty

    Journal: Cognitive Computation

    doi: 10.1007/s12559-021-09978-8

    Trained Belief Rule Base Using fmincon for Patient Survival Probability (Y) where input antecedents are X1: Patient Condition, X2: Blood Pressure, X3: Chronic Obstructive Pulmonary Disease, X4: Blood Sugar, X5: Asthma, X6: Chronic Kidney Disease, X7: Obesity, X8: Acute Respiratory Distress Syndrome, X9: Pulse Oximetry, Critical: C, Non Critical: NC, Hypertensive Crisis: HC, Very Severely Abnormal: VSA, Diabetic: D, Severe Persistent: SP, Very Severe: VS, Level III: L-III, Severe: S, Moderate: M, Normal: N, Mild: Mi, VH: Very High, H: High, M: Medium, L: Low, VL: Very Low)
    Figure Legend Snippet: Trained Belief Rule Base Using fmincon for Patient Survival Probability (Y) where input antecedents are X1: Patient Condition, X2: Blood Pressure, X3: Chronic Obstructive Pulmonary Disease, X4: Blood Sugar, X5: Asthma, X6: Chronic Kidney Disease, X7: Obesity, X8: Acute Respiratory Distress Syndrome, X9: Pulse Oximetry, Critical: C, Non Critical: NC, Hypertensive Crisis: HC, Very Severely Abnormal: VSA, Diabetic: D, Severe Persistent: SP, Very Severe: VS, Level III: L-III, Severe: S, Moderate: M, Normal: N, Mild: Mi, VH: Very High, H: High, M: Medium, L: Low, VL: Very Low)

    Techniques Used:

    Comparison of AUC of CNN-BRBES and Expert Opinion
    Figure Legend Snippet: Comparison of AUC of CNN-BRBES and Expert Opinion

    Techniques Used: Comparison



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    Image Search Results


    Trained Belief Rule Base Using fmincon for Patient Survival Probability (Y) where input antecedents are X1: Patient Condition, X2: Blood Pressure, X3: Chronic Obstructive Pulmonary Disease, X4: Blood Sugar, X5: Asthma, X6: Chronic Kidney Disease, X7: Obesity, X8: Acute Respiratory Distress Syndrome, X9: Pulse Oximetry, Critical: C, Non Critical: NC, Hypertensive Crisis: HC, Very Severely Abnormal: VSA, Diabetic: D, Severe Persistent: SP, Very Severe: VS, Level III: L-III, Severe: S, Moderate: M, Normal: N, Mild: Mi, VH: Very High, H: High, M: Medium, L: Low, VL: Very Low)

    Journal: Cognitive Computation

    Article Title: An Integrated Deep Learning and Belief Rule Base Intelligent System to Predict Survival of COVID-19 Patient under Uncertainty

    doi: 10.1007/s12559-021-09978-8

    Figure Lengend Snippet: Trained Belief Rule Base Using fmincon for Patient Survival Probability (Y) where input antecedents are X1: Patient Condition, X2: Blood Pressure, X3: Chronic Obstructive Pulmonary Disease, X4: Blood Sugar, X5: Asthma, X6: Chronic Kidney Disease, X7: Obesity, X8: Acute Respiratory Distress Syndrome, X9: Pulse Oximetry, Critical: C, Non Critical: NC, Hypertensive Crisis: HC, Very Severely Abnormal: VSA, Diabetic: D, Severe Persistent: SP, Very Severe: VS, Level III: L-III, Severe: S, Moderate: M, Normal: N, Mild: Mi, VH: Very High, H: High, M: Medium, L: Low, VL: Very Low)

    Article Snippet: In order to ensure the reliability of the rules in the initial BRB, the BRBES is trained using the non-linear optimization solver fmincon in MATLAB optimization toolbox [ ], Belief Rule-Based Adaptive Particle Swarm Optimization (BRBAPSO) [ ], and the enhanced Belief Rule-Based adaptive Differential Evolution (eBRBaDE) algorithm [ ].

    Techniques:

    Comparison of AUC of CNN-BRBES and Expert Opinion

    Journal: Cognitive Computation

    Article Title: An Integrated Deep Learning and Belief Rule Base Intelligent System to Predict Survival of COVID-19 Patient under Uncertainty

    doi: 10.1007/s12559-021-09978-8

    Figure Lengend Snippet: Comparison of AUC of CNN-BRBES and Expert Opinion

    Article Snippet: In order to ensure the reliability of the rules in the initial BRB, the BRBES is trained using the non-linear optimization solver fmincon in MATLAB optimization toolbox [ ], Belief Rule-Based Adaptive Particle Swarm Optimization (BRBAPSO) [ ], and the enhanced Belief Rule-Based adaptive Differential Evolution (eBRBaDE) algorithm [ ].

    Techniques: Comparison