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Adaptive state estimation of groundwater contaminant boundary input flux in a 2-dimensional aquifer

Journal of Groundwater Science and Engineering 2019年第4期7卷 373-382页

作者： muhammad Malik Nauman Murtuza Mehdi Asif Iqbal muhammad saifullah abu bakar Brahim Aissa Dk Nur Afiqah Jalwati Puteri Amer Farhan Rafique Faculty of Integrated Technologies University Brunei DarussalamJalan Tungku LinkGadongBE1410Bandar Seri BegawanBrunei Darussalam Department of Mechanical Engineering NED University of Engineering and TechnologyPakistan College of Science and Engineering Hamad Bin Khalifa UniversityQatar Department of Aeronautical Engineering King Abdulaziz UniversityJeddahSaudi Arabia.

In many circumstances involving heat and mass transfer issues,it is considered impractical to measure the input flux and the resulting state distribution in the ***,the need to develop techniques to provide solutions for such problems and estimate the inverse mass flux becomes *** state estimator(ASE)is increasingly becoming a popular inverse estimation technique which resolves inverse problems by incorporating the semi-Markovian concept into a Bayesian estimation technique,thereby developing an inverse input and state estimator consisting of a bank of parallel adaptively weighted Kalman *** ASE is particularly designed for a system that encompasses independent unknowns and/or random switching of input and measurement *** present study describes the scheme to estimate the groundwater input contaminant flux and its transient distribution in a conjectural two-dimensional aquifer by means of ASE,which in particular is because of its unique ability to efficiently handle the process noise giving an estimation of keeping the relative error range within 10%in 2-dimensional *** simulation results show that the proposed estimator presents decent estimation performance for both smoothly and abruptly varying input flux *** also show that ASE enjoys a better estimation performance than its competitor,Recursive Least Square Estimator(RLSE)due to its larger error tolerance in greater process noise ***'s inherent deficiency of being slower than the RLSE,resulting from the complexity of algorithm,was also *** chosen input scenarios are tested to calculate the effect of input area and both estimators show improved results with an increase in input flux area especially as sensors are moved closer to the assumed input location.

关键词： Adaptive state estimation Aquifer Contamination Groundwater Kalman filter

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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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A Hybrid Quantum Inspired Particle Swarm Optimization and Least Square Framework for Real-time Harmonic Estimation

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Journal of Modern Power Systems and Clean Energy 2021年第6期9卷 1548-1556页

作者： abu bakar Waqas muhammad Mansoor Ashraf Yasir saifullah Department of Communication Science and Engineering School of Information Science and TechnologyFudan University Electrical Engineering Department University of Engineering and Technology

The power quality is becoming an extensively addressing aspect of the power system because of the sensitive operation of the smart grid, awareness of power quality, and the equipment of modern power systems. In this paper, we have conceived a new hybrid Quantum inspired particle swarm optimization and least square(QPSO-LS) framework for real-time estimation of harmonics presented in time-varying noisy power signals. The technique has strong, robust, and reliable search capability with powerful convergence properties. The proposed approach is applied to various test systems at different signal to noise ratio(SNR) levels in the presence of uniform and Gaussian noise. The results are presented in terms of precision, computation time, and convergence characteristics. The computation time decreases by 3-5 times as compared to the existing algorithms. The technique is further authenticated by estimating harmonics of real-time current or voltage waveforms, obtained from light emitting diode(LED) lamp and axial flux permanent magnet synchronous generator(AFPMSG). The results demonstrate the superiority of QPSO-LS over other methods such as LS-based genetic algorithm(GA), particle swarm optimization(PSO), bacterial foraging optimization(BFO), artificial bee colony(ABC), and biogeography based optimization with recursive LS(BBO-RLS) algorithms, in terms of providing satisfactory solutions with a significant amount of robustness and computation efficiency.

关键词： Harmonic estimation power quality particle swarm optimization(PSO) least square(LS) smart grid

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Risk of infection with arboviruses in a healthy population in Pakistan based on seroprevalence

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VIROLOGICA SINICA 2024年第3期39卷 369-377页

作者： Chen, Shengyao Saqib, muhammad Khan, Hafiz Sajid Bai, Yuan Ashfaq, Usman Ali Mansoor, muhammad Khalid Moming, abulimti Liu, Jing Zhou, Min Niazi, saifullah Khan Wu, Qiaoli Sial, Awais-Ur-Rahman Tang, Shuang Sarfraz, muhammad Hassan Javed, Aneela Hayat, Sumreen Khurshid, Mohsin Khan, Iahtasham Athar, muhammad Ammar Taj, Zeeshan Zhang, Bo Deng, Fei Zohaib, Ali Shen, Shu Chinese Acad Sci Key Lab Virol Wuhan 430071 Peoples R China Chinese Acad Sci Wuhan Inst Virol Natl Virus Resource Ctr Wuhan 430071 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Hubei Jiangxia Lab Wuhan 430200 Peoples R China Univ Agr Faisalabad Fac Vet Sci Faisalabad 38040 Pakistan Childrens Hosp Faisalabad Faisalabad 38000 Pakistan Govt Coll Univ Faisalabad Dept Bioinformat & Biotechnol Faisalabad 38000 Pakistan Islamia Univ Bahawalpur Fac Vet & Anim Sci Dept Microbiol Bahawalpur 63100 Pakistan Chinese Acad Sci Wuhan Inst Virol Ctr Biosafety Mega Sci Key Lab Special Pathogens & Biosafety Wuhan 430071 Hubei Peoples R China Armed Forces Inst Pathol AFIP Rawalpindi 46000 Pakistan Pir Mehr Ali Shah Arid Agr Univ Fac Vet & Anim Sci Dept Clin Studies Rawalpindi 46300 Pakistan Govt Coll Univ Faisalabad Inst Microbiol Faisalabad 38000 Pakistan Natl Univ Sci & Technol Atta Ur Rahman Sch Appl Biosci Islamabad 44000 Pakistan Univ Vet & Anim Sci Dept Clin Sci Lahore Subcampus Jhang 35200 Pakistan Natl Med Ctr Dept Mol Pathol DHA Phase 1 Karachi 75500 Pakistan

Infectious diseases caused by arboviruses are a public health concern in Pakistan. However, studies on data prevalence and threats posed by arboviruses are limited. This study investigated the seroprevalence of arboviruses in a healthy population in Pakistan, including severe fever with thrombocytopenia syndrome virus (SFTSV), Crimean-Congo hemorrhagic fever virus (CCHFV), Tamdy virus (TAMV), and Karshi virus (KSIV) based on a newly established luciferase immunoprecipitation system (LIPS) assays, and Zika virus (ZIKV) by enzyme-linked immunosorbent assays (ELISA). Neutralizing activities against these arboviruses were further examined from the antibody positive samples. The results showed that the seroprevalence of SFTSV, CCHFV, TAMV, KSIV, and ZIKV was 17.37%, 7.58%, 4.41%, 1.10%, and 6.48%, respectively, and neutralizing to SFTSV (1.79%), CCHFV (2.62%), and ZIKV (0.69%) were identified, as well as to the SFTSV-related Guertu virus (GTV, 0.83%). Risk factors associated with the incidence of exposure and levels of antibody response were analyzed. Moreover, co-exposure to different arboviruses was demonstrated, as thirty-seven individuals were having antibodies against multiple viruses and thirteen showed neutralizing activity. Males, individuals aged <= 40 years, and outdoor workers had a high risk of exposure to arboviruses. All these results reveal the substantial risks of infection with arboviruses in Pakistan, and indicate the threat from co-exposure to multiple arboviruses. The findings raise the need for further epidemiologic investigation in expanded regions and populations and the necessity to improve health surveillance in Pakistan.

关键词： Arbovirus Pakistan Seroprevalence Tick -borne virus Mosquito -borne virus

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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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