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Comparison of Cox proportional hazards model,Cox proportional hazards with time-varying coefficients model,and lognormal accelerated failure time model:Application in time to event analysis of melioidosis patients

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Asian Pacific Journal of Tropical Medicine 2022年第3期15卷 128-134页

作者： Kamaruddin Mardhiah Nadiah Wan-Arfah Nyi Nyi Naing muhammad radzi abu hassan Huan-Keat Chan Faculty of Entrepreneurship and Business Universiti Malaysia KelantanKota BharuKelantanMalaysia Faculty of Health Sciences Universiti Sultan Zainal AbidinKuala TerengganuTerengganuMalaysia Faculty of Medicine Universiti Sultan Zainal AbidinKuala TerengganuTerengganuMalaysia Clinical Research Center Hospital Sultanah BahiyahMinistry of Health MalaysiaAlor SetarKedahMalaysia

Objective:To compare the prognostic factors of mortality among melioidosis patients between lognormal accelerated failure time(AFT),Cox proportional hazards(PH),and Cox PH with time-varying coefficient(TVC)***:A retrospective study was conducted from 2014 to 2019 among 453 patients who were admitted to Hospital Sultanah Bahiyah,Kedah and Hospital Tuanku Fauziah,Perlis in Northern Malaysia due to confirmed-cultured *** prognostic factors of mortality from melioidosis were obtained from AFT survival analysis,and Cox’s models and the findings were compared by using the goodness of fit *** analyses were done by using Stata SE version ***:A total of 242 patients(53.4%)*** this study,the median survival time of melioidosis patients was 30.0 days(95%CI 0.0-60.9).Six significant prognostic factors were identified in the Cox PH model and Cox PH-TVC *** AFT survival analysis,a total of seven significant prognostic factors were *** results were found to be only a slight difference between the identified prognostic factors among the *** survival showed better results compared to Cox's models,with the lowest Akaike information criteria and best fitted Cox-snell ***:AFT survival analysis provides more reliable results and can be used as an alternative statistical analysis for determining the prognostic factors of mortality in melioidosis patients in certain situations.

关键词： Cox proportional hazards Time-dependent Time-varying Accelerated failure time survival analysis Lognormal Parametric model Time-to-event Melioidosis Mortality

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Predictors of in-hospital mortality by logistic regression analysis among melioidosis patients in Northern Malaysia:A retrospective study

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Asian Pacific Journal of Tropical Medicine 2021年第8期14卷 356-363页

作者： Kamaruddin Mardhiah Nadiah Wan-Arfah Nyi Nyi Naing muhammad radzi abu hassan Huan-Keat Chan Faculty of Entrepreneurship and Business Universiti Malaysia KelantanKota BharuKelantanMalaysia Faculty of Health Sciences Universiti Sultan Zainal AbidinGong Badak CampusKuala TerengganuTerengganuMalaysia Faculty of Medicine Universiti Sultan Zainal AbidinKuala TerengganuTerengganuMalaysia Clinical Research Center Hospital Sultanah BahiyahMinistry of Health MalaysiaAlor SetarKedahMalaysia

Objective:To identify the predictors of mortality among in-hospital melioidosis ***:A total of 453 patients in Hospital Sultanah Bahiyah,Kedah,and Hospital Tuanku Fauziah,Perlis with culture-confirmed melioidosis were retrospectively included in the *** multiple logistic regression was used to obtain the final model of predictors of mortality from *** analysis was performed using STATA/SE ***:A total of 50.11%(227/453)of the patients died at the hospital,and a majority(86.75%,393/453)of cases were *** logistic regression estimated that the bacteremic type of melioidosis,low platelet count,abnormal white blood cell counts,and increased urea value were predictors of *** results showed that bacteremic melioidosis increased the risk of death by 4.39 times(OR 4.39,95%CI 1.83-10.55,P=0.001)compared to non-bacteremic *** on laboratory test,the adjusted ORs from the final model showed that all three blood investigations were included as the associated factors of mortality for the disease[high white blood cell(>10×10^(9)/L):OR 2.43,95%CI1.41-4.17,P7800μmol/L):OR 5.53,95%CI 2.50-12.30,P<0.001;and low level of urea(<2500μmol/L):OR 3.52,95%CI 1.71-7.23,P=0.001].Conclusions:Routine blood investigations during a hospital admission can early identify predictors of mortality in melioidosis patients.

关键词： Melioidosis Infectious disease Mortality Predictors Prognostic factors Logistic model

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Germline mutation analysis of MLH1 and MSH2 in Malaysian Lynch syndrome patients

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World Journal of Gastroenterology 2012年第8期18卷 814-820页

作者： Mohd Nizam Zahary Ravindran Ankathi Human Genome Centre Gurjeet Kaur muhammad radzi abu hassan Harjinder Singh Venkatesh R Naik School of Medical Sciences University Sains Malaysia Health Campus16150 Kubang KerianKelantanMalaysia Institute for Research in Molecular Medicine University Sains Malaysia11800 PenangMalaysia Internal Medicine Department Hospital Alor Star05460 Alor StarKedahMalaysia Department of Medicine Hospital Queen Elizabeth88586 Kota KinabaluSabahMalaysia Department of Pathology School of Medical SciencesUniversity Sains Malaysia Health Campus16150 Kubang KerianKelantanMalaysia

AIM: To investigate the protein expression profi le of mismatch repair (MMR) genes in suspected cases of Lynch syndrome and to characterize the associated germline mutations. METHODS: Immunohistochemical analysis of tumor samples was performed to determine the protein expression profile of MMR protein. Germline mutation screening was carried out on peripheral blood samples. The entire exon regions of MLH1 and MSH2 geneswere amplifi ed by polymerase chain reaction, screened by denaturing high performance liquid chromatography (dHPLC) and analyzed by DNA sequencing to characterize the germline mutations. RESULTS: Three out of 34 tissue samples (8.8%) and four out of 34 tissue samples (11.8%) showed loss of nuclear staining by immunohistochemistry, indicating the absence of MLH1 and MSH2 protein expression in carcinoma cells, respectively. dHPLC analysis followed by DNA sequencing showed these samples to have germline mutations of MSH2 gene. However, no deleterious mutations were identifi ed in any of the 19 exons or coding regions of MLH1 gene, but we were able to identify MLH1 promoter polymorphism, -93G > A (rs1800734), in 21 out of 34 patients (61.8%). We identified one novel mutation, transversion mutation c.2005G > C, which resulted in a missense mutation (Gly669Arg), a transversion mutation in exon 1, c.142G > T, which resulted in a nonsense mutation (Glu48Stop) and splice-site mutation, c.2006-6T > C, which was adjacent to exon 13 of MSH2 gene. CONCLUSION: Germline mutations were identified in four Malaysian Lynch syndrome patients. Immunohistochemical analysis of tumor tissue proved to be a good pre-screening test before proceeding to germline mutation analysis of DNA MMR genes.

关键词：基因启动子突变分析胚系突变马来西亚综合征患者变性高效液相色谱 DNA测序

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SNR and RSSI Based an Optimized Machine Learning Based Indoor Localization Approach:Multistory Round Building Scenario over LoRa Network

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Computers, Materials & Continua 2024年第8期80卷 1927-1945页

作者： muhammad Ayoub Kamal muhammad Mansoor Alam Aznida abu Bakar Sajak Mazliham Mohd Su’ud Malaysian Institute of Information Technology(MIIT) Universiti Kuala LumpurKuala Lumpur50250Malaysia Faculty of Computing and Informatics Multimedia UniversityCyberjaya63100Malaysia Depertment of Computer Science DHA Suffa UniversityKarachiSindh75500Pakistan Riphah Institute of System Engineering(RISE) Faculty of ComputingRiphah International UniversityIslamabad46000Pakistan Malaysian France Institute(MFI) Universiti Kuala LumpurKuala Lumpur50250Malaysia Faculty of Engineering and Information Technology School of Computer ScienceUniversity of Technology SydneyUltimoNSW 2007Australia

In situations when the precise position of a machine is unknown,localization becomes *** research focuses on improving the position prediction accuracy over long-range(LoRa)network using an optimized machine learning-based *** order to increase the prediction accuracy of the reference point position on the data collected using the fingerprinting method over LoRa technology,this study proposed an optimized machine learning(ML)based *** signal strength indicator(RSSI)data from the sensors at different positions was first gathered via an experiment through the LoRa network in a multistory round layout *** noise factor is also taken into account,and the signal-to-noise ratio(SNR)value is recorded for every RSSI *** study concludes the examination of reference point accuracy with the modified KNN method(MKNN).MKNN was created to more precisely anticipate the position of the reference *** findings showed that MKNN outperformed other algorithms in terms of accuracy and complexity.

关键词： Indoor localization MKNN LoRa machine learning classification RSSI SNR localization

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Application of deep learning in iron ore sintering process:a review

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Journal of Iron and Steel Research(International) 2024年第5期31卷 1033-1049页

作者： Yu-han Gong Chong-hao Wang Jie Li muhammad Nasiruddin Mahyuddin Mohamad Tarmizi abu Seman School of Electrical and Electronic Engineering Universiti Sains Malaysia14300 Nibong TebalPenangMalaysia College of Electrical Engineering North China University of Science and TechnologyTangshan 063210HebeiChina Technology Transfer Center North China University of Science and TechnologyTangshan 063210HebeiChina School of Metallurgy and Energy North China University of Science and TechnologyTangshan 063210HebeiChina

In the wake of the era of big data,the techniques of deep learning have become an essential research direction in the machine learning field and are beginning to be applied in the steel *** sintering process is an extremely complex industrial *** the main process of the blast furnace ironmaking industry,it has great economic value and environmental protection significance for iron and steel *** is also one of the fields where deep learning is still in the exploration *** order to explore the application prospects of deep learning techniques in iron ore sintering,a comprehensive summary and conclusion of deep learning models for intelligent sintering were presented after reviewing the sintering process and deep learning models in a large number of research ***,the mechanisms and characteristics of parameters in sintering processes were introduced and analysed in detail,and then,the development of iron ore sintering simulation techniques was ***,deep learning techniques were introduced,including commonly used models of deep learning and their ***,the current status of applications of various types of deep learning models in sintering processes was elaborated in detail from the aspects of prediction,controlling,and optimisation of key *** speaking,deep learning models that could be more effectively implemented in more situations of the sintering and even steel industry chain will promote the intelligent development of the metallurgical industry.

关键词： Deep learning Sintering process Modelling Simulation technology Intelligent sintering

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An Innovative Approach Using TKN-Cryptology for Identifying the Replay Assault

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Computers, Materials & Continua 2024年第1期78卷 589-616页

作者： Syeda Wajiha Zahra muhammad Nadeem Ali Arshad Saman Riaz muhammad abu Bakr Ashit Kumar Dutta Zaid Alzaid Badr Almutairi Sultan Almotairi Department of Computer Science Alhamd Islamic UniversityIslamabad44000Pakistan Department of Computer Science and Technology University of Science and Technology BeijingBeijing100083China Department of Computer Science National University of TechnologyIslamabad44000Pakistan Department of Electrical Engineering National University of TechnologyIslamabad44000Pakistan Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityRiyadh13713Saudi Arabia Department of Computer Science Faculty of Computer and Information SystemsIslamic University of MadinahMedinah42351Saudi Arabia Department of Information Technology College of Computer Sciences and Information Technology CollegeMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Natural and Applied Sciences Faculty of Community CollegeMajmaah UniversityMajmaah11952Saudi Arabia

Various organizations store data online rather than on physical *** the number of user’s data stored in cloud servers increases,the attack rate to access data from cloud servers also *** researchers worked on different algorithms to protect cloud data from replay *** of the papers used a technique that simultaneously detects a full-message and partial-message replay *** study presents the development of a TKN(Text,Key and Name)cryptographic algorithm aimed at protecting data from replay *** program employs distinct ways to encrypt plain text[P],a user-defined Key[K],and a Secret Code[N].The novelty of the TKN cryptographic algorithm is that the bit value of each text is linked to another value with the help of the proposed algorithm,and the length of the cipher text obtained is twice the length of the original *** the scenario that an attacker executes a replay attack on the cloud server,engages in cryptanalysis,or manipulates any data,it will result in automated modification of all associated values inside the *** mechanism has the benefit of enhancing the detectability of replay ***,the attacker cannot access data not included in any of the papers,regardless of how effective the attack strategy *** the end of paper,the proposed algorithm’s novelty will be compared with different algorithms,and it will be discussed how far the proposed algorithm is better than all other algorithms.

关键词： Replay attack malware message attack file encryption cryptology data security

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National guidelines for the diagnosis and treatment of hilar cholangiocarcinoma

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World Journal of Gastroenterology 2024年第9期30卷 1018-1042页

作者： Faisal Saud Dar Zaigham Abbas Irfan Ahmed muhammad Atique Usman Iqbal Aujla muhammad Azeemuddin Zeba Aziz abu Bakar Hafeez Bhatti Tariq Ali Bangash Amna Subhan Butt Osama Tariq Butt Abdul Wahab Dogar Javed Iqbal Farooqi Faisal Hanif Jahanzaib Haider Siraj Haider Syed Mujahid hassan Adnan Abdul Jabbar Aman Nawaz Khan muhammad Shoaib Khan muhammad Yasir Khan Amer Latif Nasir hassan Luck Ahmad Karim Malik Kamran Rashid Sohail Rashid Mohammad Salih Abdullah Saeed Amjad Salamat Ghias-un-Nabi Tayyab Aasim Yusuf Haseeb Haider Zia Ammara Naveed Department of Hepatopancreatic Biliary Surgery&Liver Transplant Pakistan Kidney and Liver Institute&Research CentreLahore 54000Pakistan Department of Hepatogastroenterology and Liver Transplantation Dr.Ziauddin University HospitalKarachi 75600SindhPakistan University of Aberdeen Aberdeen B243FXUnited Kingdom Department of Pathology Pakistan Kidney and Liver Institute&Research CentreLahore 54000Pakistan Department of Gastroenterology&Hepatology Pakistan Kidney and Liver Institute&Research CentreLahore 54000Pakistan Department of Radiology Aga Khan UniversityKarachi 74800Pakistan Department of Oncology Hameed Latif HospitalLahore 54000Pakistan Division of Hepatopancreatic Biliary Surgery&Liver Transplantation Shifa International HospitalIslamabad 44000Pakistan Department of Hepatopancreatic Biliary Surgery&Liver Transplant Shaikh Zayed Hospital and Post Graduate Medical InstituteLahore 54000Pakistan Department of Medicine Aga Khan University HospitalKarachi 74800Pakistan Department of Liver Transplant Pir Abdul Qadir Shah Jeelani Institute of Medical SciencesGambat 66020Pakistan Department of Medicine&Gastroenterology Lifecare Hospital and Research CentrePeshawar 25000Khyber PakhtunkhwaPakistan Department of Hepatopancreatobiliary&Liver Transplant Bahria International HospitalLahore 54000Pakistan Department of Surgery Hepatopancreatobiliary&Liver TransplantDow University of Health SciencesKarachi 74800Pakistan Department of Gastroenterology Hepatology&NutritionPir Abdul Qadir Shah Jeelani Institute of Medical SciencesGambat 66020Pakistan Department of Oncology Dr.Ziauddin HospitalKarachi 74800Pakistan Department of Radiology Rehman Medical InstitutePeshawar 25000Pakistan Army Liver Transplant Unit Pak Emirates Military HospitalRawalpindi 46000Pakistan Department of Gastroenterology Sindh Institute of Urology and TransplantationKarachi 75500Pakistan Rashid Nursing Home and Cancer Clinic Rashid Nursing Home and Cancer ClinicRawalpindi 46000Pakistan Department of Gastroentero

A consensus meeting of national experts from all major national hepatobiliary centres in the country was held on May 26,2023,at the Pakistan Kidney and Liver Institute&Research Centre(PKLI&RC)after initial consultations with the *** Pakistan Society for the Study of Liver Diseases(PSSLD)and PKLI&RC jointly organised this *** effort was based on a comprehensive literature review to establish national practice guidelines for hilar cholangiocarcinoma(hCCA).The consensus was that hCCA is a complex disease and requires a multidisciplinary team approach to best manage these *** coordinated effort can minimise delays and give patients a chance for curative treatment and effective *** diagnostic and staging workup includes high-quality computed tomography,magnetic resonance imaging,and magnetic resonance *** cytology or biopsy utilizing endoscopic retrograde cholangiopancreatography is a mainstay for ***,histopathologic confirmation is not always required before *** ultrasound with fine needle aspiration of regional lymph nodes and positron emission tomography scan are valuable adjuncts for *** only curative treatment is the surgical resection of the biliary tree based on the Bismuth-Corlette *** patients with unresectable hCCA can be considered for liver *** chemotherapy should be offered to patients with a high risk of *** use of preoperative biliary drainage and the need for portal vein embolisation should be based on local multidisciplinary *** with acute cholangitis can be drained with endoscopic or percutaneous biliary *** chemotherapy with cisplatin and gemcitabine has shown improved survival in patients with irresectable and recurrent hCCA.

关键词： Hilar cholangiocarcinoma Bismuth-Corlette classification Memorial Sloan Kettering Cancer Centre Staging Preoperative biliary drainage Portal vein embolisation Surgical resection Hepatectomy

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Federated Machine Learning Based Fetal Health Prediction Empowered with Bio-Signal Cardiotocography

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Computers, Materials & Continua 2024年第3期78卷 3303-3321页

作者： muhammad Umar Nasir Omar Kassem Khalil Karamath Ateeq Bassam SaleemAllah Almogadwy muhammad Adnan Khan muhammad Hasnain Azam Khan muhammad Adnan Department of Computer Sciences Bahria University Lahore CampusLahore54000Pakistan Faculty of Information Technology Liwa CollegeAbu Dhabi00000United Arab Emirates Department of Computing Skyline University CollegeSharjah1797United Arab Emirates Department of Computer Science Taibah UniversityMedina42353Saudi Arabia Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Engineering and Development Dubizzle LabsLahore54000Pakistan Department of Software Faculty of Artificial Intelligence and SoftwareGachon UniversitySeongnam-si13120Korea

Cardiotocography measures the fetal heart rate in the fetus during pregnancy to ensure physical health because cardiotocography gives data about fetal heart rate and uterine shrinkages which is very beneficial to detect whether the fetus is normal or suspect or *** cardiotocography measures infer wrongly and give wrong predictions because of human *** traditional way of reading the cardiotocography measures is the time taken and belongs to numerous human errors as *** condition is very important to measure at numerous stages and give proper medications to the fetus for its *** the current period Machine learning(ML)is a well-known classification strategy used in the biomedical field on various issues because ML is very fast and gives appropriate results that are better than traditional *** techniques play a pivotal role in detecting fetal disease in its early *** research article uses Federated machine learning(FML)and ML techniques to classify the condition of the *** study proposed a model for the detection of bio-signal cardiotocography that uses FML and ML techniques to train and test the ***,the proposed model of FML used numerous data preprocessing techniques to overcome data deficiency and achieves 99.06%and 0.94%of prediction accuracy and misprediction rate,respectively,and parallel the proposed model applying K-nearest neighbor(KNN)and achieves 82.93%and 17.07%of prediction accuracy and misprediction accuracy,***,by comparing both models FML outperformed the KNN technique and achieved the best and most appropriate prediction results as compared with previous studies the proposed study achieves the best and most accurate results.

关键词： Cardiotocography ML FML fetal disease bio-signal

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Cervical Cancer Prediction Empowered with Federated Machine Learning

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Computers, Materials & Continua 2024年第4期79卷 963-981页

作者： muhammad Umar Nasir Omar Kassem Khalil Karamath Ateeq Bassam SaleemAllah Almogadwy M.A.Khan Khan muhammad Adnan Department of Computer Sciences Bahria University Lahore CampusLahore54000Pakistan Faculty of Information Technology Liwa CollegeAbu Dhabi20009UAE Department of Computing Skyline University CollegeSharjah999041UAE Department of Computer Science Taibah UniversityMedina42315Saudi Arabia Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore54000Pakistan Department of Software Faculty of Artificial Intelligence and SoftwareGachon UniversitySeongnam13120Korea

Cervical cancer is an intrusive cancer that imitates various women around the world. Cervical cancer ranks in thefourth position because of the leading death cause in its premature stages. The cervix which is the lower end of thevagina that connects the uterus and vagina forms a cancerous tumor very slowly. This pre-mature cancerous tumorin the cervix is deadly if it cannot be detected in the early stages. So, in this delineated study, the proposed approachuses federated machine learning with numerous machine learning solvers for the prediction of cervical cancer totrain the weights with varying neurons empowered fuzzed techniques to align the neurons, Internet of MedicalThings (IoMT) to fetch data and blockchain technology for data privacy and models protection from hazardousattacks. The proposed approach achieves the highest cervical cancer prediction accuracy of 99.26% and a 0.74%misprediction rate. So, the proposed approach shows the best prediction results of cervical cancer in its early stageswith the help of patient clinical records, and all medical professionals will get beneficial diagnosing approachesfrom this study and detect cervical cancer in its early stages which reduce the overall death ratio of women due tocervical cancer.

关键词： Cervical cancer federated machine learning neurons blockchain technology

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Smart prediction of liquefaction-induced lateral spreading

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第6期16卷 2310-2325页

作者： muhammad Nouman Amjad Raja Tarek Abdoun Waleed El-Sekelly New York University(NYU)abu Dhabi Abu Dhabi129188United Arab Emirates University of Management and Technology Lahore54372Pakistan Department of Civil and Environmental Eng. Rensselaer Polytechnic Institute(RPI)1108th StreetJEC 4049TroyNY12180USA Department of Structural Engineering Mansoura UniversityMansoura35516Egypt

The prediction of liquefaction-induced lateral spreading/displacement(Dh)is a challenging task for civil/geotechnical *** this study,a new approach is proposed to predict Dh using gene expression programming(GEP).Based on statistical reasoning,individual models were developed for two topographies:free-face and gently sloping *** with a comparison with conventional approaches for predicting the Dh,four additional regression-based soft computing models,*** process regression(GPR),relevance vector machine(RVM),sequential minimal optimization regression(SMOR),and M5-tree,were developed and compared with the GEP *** results indicate that the GEP models predict Dh with less bias,as evidenced by the root mean square error(RMSE)and mean absolute error(MAE)for training(i.e.1.092 and 0.815;and 0.643 and 0.526)and for testing(i.e.0.89 and 0.705;and 0.773 and 0.573)in free-face and gently sloping ground topographies,*** overall performance for the free-face topology was ranked as follows:GEP>RVM>M5-tree>GPR>SMOR,with a total score of 40,32,24,15,and 10,*** the gently sloping condition,the performance was ranked as follows:GEP>RVM>GPR>M5-tree>SMOR with a total score of 40,32,21,19,and 8,***,the results of the sensitivity analysis showed that for both free-face and gently sloping ground,the liquefiable layer thickness(T_(15))was the major parameter with percentage deterioration(%D)value of 99.15 and 90.72,respectively.

关键词： Lateral spreading Intelligent modeling Gene expression programming(GEP) Closed-form solution Feature importance

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