Matches in SemOpenAlex for { <https://semopenalex.org/work/W1980293156> ?p ?o ?g. }
- W1980293156 endingPage "3964" @default.
- W1980293156 startingPage "3955" @default.
- W1980293156 abstract "Hybrid system is a potential tool to deal with construction engineering and management problems. This study proposes an optimized hybrid artificial intelligence model to integrate a fast messy genetic algorithm (fmGA) with a support vector machine (SVM). The fmGA-based SVM (GASVM) is used for early prediction of dispute propensity in the initial phase of public–private partnership projects. Particularly, the SVM mainly provides learning and curve fitting while the fmGA optimizes SVM parameters. Measures in term of accuracy, precision, sensitivity, specificity, and area under the curve and synthesis index are used for performance evaluation of proposed hybrid intelligence classification model. Experimental comparisons indicate that GASVM achieves better cross-fold prediction accuracy compared to other baseline models (i.e., CART, CHAID, QUEST, and C5.0) and previous works. The forecasting results provide the proactive-warning and decision-support information needed to manage potential disputes." @default.
- W1980293156 created "2016-06-24" @default.
- W1980293156 creator A5026969387 @default.
- W1980293156 creator A5043651248 @default.
- W1980293156 creator A5071656520 @default.
- W1980293156 creator A5074387638 @default.
- W1980293156 date "2014-06-01" @default.
- W1980293156 modified "2023-10-18" @default.
- W1980293156 title "Optimizing parameters of support vector machine using fast messy genetic algorithm for dispute classification" @default.
- W1980293156 cites W1505686907 @default.
- W1980293156 cites W1543810117 @default.
- W1980293156 cites W1585021961 @default.
- W1980293156 cites W1966602182 @default.
- W1980293156 cites W1969334115 @default.
- W1980293156 cites W1978531156 @default.
- W1980293156 cites W1979540177 @default.
- W1980293156 cites W1979675413 @default.
- W1980293156 cites W1982969948 @default.
- W1980293156 cites W1984308300 @default.
- W1980293156 cites W1992856986 @default.
- W1980293156 cites W1993839467 @default.
- W1980293156 cites W1999787261 @default.
- W1980293156 cites W2000649639 @default.
- W1980293156 cites W2006520016 @default.
- W1980293156 cites W2008686758 @default.
- W1980293156 cites W2015493438 @default.
- W1980293156 cites W2020355555 @default.
- W1980293156 cites W2027043498 @default.
- W1980293156 cites W2027083421 @default.
- W1980293156 cites W2028193856 @default.
- W1980293156 cites W2034781672 @default.
- W1980293156 cites W2036657109 @default.
- W1980293156 cites W2038209130 @default.
- W1980293156 cites W2039568194 @default.
- W1980293156 cites W2059536239 @default.
- W1980293156 cites W2062540930 @default.
- W1980293156 cites W2064528384 @default.
- W1980293156 cites W2065339250 @default.
- W1980293156 cites W2066592057 @default.
- W1980293156 cites W2072925301 @default.
- W1980293156 cites W2072962544 @default.
- W1980293156 cites W2073817142 @default.
- W1980293156 cites W2074669169 @default.
- W1980293156 cites W2086691529 @default.
- W1980293156 cites W2088249484 @default.
- W1980293156 cites W2091488899 @default.
- W1980293156 cites W2091621250 @default.
- W1980293156 cites W2092091083 @default.
- W1980293156 cites W2095906349 @default.
- W1980293156 cites W2099539305 @default.
- W1980293156 cites W2100337447 @default.
- W1980293156 cites W2103278824 @default.
- W1980293156 cites W2116825089 @default.
- W1980293156 cites W2118286367 @default.
- W1980293156 cites W2119304762 @default.
- W1980293156 cites W2126763699 @default.
- W1980293156 cites W2132664750 @default.
- W1980293156 cites W2137634615 @default.
- W1980293156 cites W2137768994 @default.
- W1980293156 cites W2141854801 @default.
- W1980293156 cites W2147379111 @default.
- W1980293156 cites W2147953360 @default.
- W1980293156 cites W2148061495 @default.
- W1980293156 cites W2151203917 @default.
- W1980293156 cites W2156224628 @default.
- W1980293156 cites W2164686541 @default.
- W1980293156 cites W2170505850 @default.
- W1980293156 doi "https://doi.org/10.1016/j.eswa.2013.12.035" @default.
- W1980293156 hasPublicationYear "2014" @default.
- W1980293156 type Work @default.
- W1980293156 sameAs 1980293156 @default.
- W1980293156 citedByCount "66" @default.
- W1980293156 countsByYear W19802931562014 @default.
- W1980293156 countsByYear W19802931562015 @default.
- W1980293156 countsByYear W19802931562016 @default.
- W1980293156 countsByYear W19802931562017 @default.
- W1980293156 countsByYear W19802931562018 @default.
- W1980293156 countsByYear W19802931562019 @default.
- W1980293156 countsByYear W19802931562020 @default.
- W1980293156 countsByYear W19802931562021 @default.
- W1980293156 countsByYear W19802931562022 @default.
- W1980293156 countsByYear W19802931562023 @default.
- W1980293156 crossrefType "journal-article" @default.
- W1980293156 hasAuthorship W1980293156A5026969387 @default.
- W1980293156 hasAuthorship W1980293156A5043651248 @default.
- W1980293156 hasAuthorship W1980293156A5071656520 @default.
- W1980293156 hasAuthorship W1980293156A5074387638 @default.
- W1980293156 hasConcept C11413529 @default.
- W1980293156 hasConcept C119857082 @default.
- W1980293156 hasConcept C12267149 @default.
- W1980293156 hasConcept C124101348 @default.
- W1980293156 hasConcept C127413603 @default.
- W1980293156 hasConcept C154945302 @default.
- W1980293156 hasConcept C16023879 @default.
- W1980293156 hasConcept C21200559 @default.
- W1980293156 hasConcept C24326235 @default.
- W1980293156 hasConcept C41008148 @default.
- W1980293156 hasConcept C84525736 @default.