Translation components API.

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GET /api/translations/libo_ui-master/nlpsolverhelpencomsunstarcompcalcnlpsolver/gu/units/?format=api
HTTP 200 OK
Allow: GET, POST, HEAD, OPTIONS
Content-Type: application/json
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                "<bookmark_value>Solver for Nonlinear Problems;Options</bookmark_value>"
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                "Size of Swarm"
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                "… defines the number of individuals to participate in the learning process. Each individual finds its own solutions and contributes to the overall knowledge."
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                "Learning Cycles"
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                "શીખવાનું ચક્ર"
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                "Variable Bounds Guessing"
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                "If enabled (default), the algorithm tries to find variable bounds by looking at the starting values."
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                "જો સક્રિય થયેલ હોય (મૂળભૂત), અલગોરિધમ શરૂઆતની કિંમતો પર જોઇને વેરિએબલ બાઉન્ડ્સને શોધવા માટે પ્રયત્ન કરે છે."
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                "Variable Bounds Threshold"
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                "When guessing variable bounds, this threshold specifies, how the initial values are shifted to build the bounds. For an example how these values are calculated, please refer to the Manual in the Wiki."
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                "જ્યારે વેરિએબલ બાઉન્ડ્સને ધારી રહ્યા હોય, ત્યારે આ થ્રેશોલ્ડ સ્પષ્ટ થાય છે, કેવી રીતે પ્રારંભિક કિંમતો બાઉન્ડ્સને બનાવવા માટે ખસેડાય છે. ઉદાહરણ તરીકે કેવી રીતે કિંમતોની ગણતરી થાય છે, મહેરબાની કરીને વિકિમાં પુસ્તિકાનો સંદર્ભ લો."
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            "source": [
                "Use ACR Comparator"
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                "ACR સંતુલકને વાપરો"
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            "source": [
                "If <emph>disabled</emph> (default), the BCH Comparator is used. It compares two individuals by first looking at their constraint violations and only if those are equal, it measures their current solution."
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                "જો <emph>નિષ્ક્રિય થયેલ</emph> હોય તો (મૂળભૂત), BCH સંતુલક વાપરેલ છે. તે તેમની મર્યાદા ભંગને પ્રથમ જોઇને બે વ્યક્તિગતોની સરખામણી કરે છે અને ફક્ત જો તે સરખા હોય તો, તે તેનાં વર્તમાન ઉકેલ ને માપે છે."
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                "If <emph>enabled</emph>, the ACR Comparator is used. It compares two individuals dependent on the current iteration and measures their goodness with knowledge about the libraries worst known solutions (in regard to their constraint violations)."
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                "જો <emph>સક્રિય થયેલ હોય</emph> તો, ACR સંતુલક વાપરેલ છે. તે હાલનાં પૂનરાવર્તન પર બે વ્યક્તિગત આધારની સરખામણી કરે છે અને લાઇબ્રેરીનાં ખરાબ જાણીતા ઉકેલો વિશે જ્ઞાન સાથે તેની ભલાઇને માપે છે (તેમની મર્યાદા ભંગ સંદર્ભે)."
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                "If this number of individuals found solutions within a close range, the iteration is stopped and the best of these values is chosen as optimal."
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                "If <emph>enabled</emph>, an additional dialog is shown during the solving process which gives information about the current progress, the level of stagnation, the currently best known solution as well as the possibility, to stop or resume the solver."
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                "DE: Crossover Probability"
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                "SCO-specific Options"
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                "There is also a list of constraints you can use to restrict the possible range of solutions or to penalize certain conditions. However, in case of the evolutionary solvers DEPS and SCO, these constraints are also used to specify bounds on the variables of the problem. Due to the random nature of the algorithms, it is <emph>highly recommended</emph> to do so and give upper (and in case \"Assume Non-Negative Variables\" is turned off also lower) bounds for all variables. They don't have to be near the actual solution (which is probably unknown) but should give a rough indication of the expected size (0 ≤ var ≤ 1 or maybe -1000000 ≤ var ≤ 1000000)."
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                "ત્યાં પરિમાણોની યાદી છે જે અમુક શરતોની સજા કરવા માટે  અથવા શક્ય ઉકેલોની સીમાને મર્યાદિત કરવા માટે વાપરી શકો છો. છતાંપણ, ઇવોલ્યુશનરી સોલ્વર DEPS અને SCO ની સ્થિતિમાં, આ પરિમાણો સમસ્યાનાં ચલો પર બાઉન્ડ્સને સ્પષ્ટ કરવા માટે પણ વાપરેલ છે. અલગોરિધમનાં ગમે તેમ વર્ણતૂક દરમ્યાન, તે આવું કરવા માટે <emph>ઉચ્ચ રીતે અગ્રહણીય</emph> છે અને બધા ચલો માટે ઉચ્ચ (અને \"બિન-નકારાત્મક ચલો ધારો\" વાળી સ્થિતિમાં બંધ થઇ જાય પણ તે નીચુ છે) બાઉન્ડ્સને આપે છે. તેઓની પાસે નજીકનો ચોક્કસ ઉકેલ નથી (કે જે શક્ય રીતે અજ્ઞાત છે) પરંતુ ઇચ્છિત માપની સૂચના આપવી જોઇએ (0 ≤ var ≤ 1 અથવા કદાચ -1000000 ≤ var ≤ 1000000)."
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                "Bounds are specified by selecting one or more variables (as range) on the left side and entering a numerical value (not a cell or a formula) on the right side. That way you can also choose one or more variables to be <emph>Integer</emph> or <emph>Binary</emph> only."
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                "બાઉન્ડ્સ એ ડાબી બાજુ પર એક અથવા વધારે વેરિએબલ (સીમા તરીકે) ને પસંદ કરીને સ્પષ્ટ થયેલ છે અને જમણી બાજુ પર આંકડાકીય કિંમતને દાખલ કરી રહ્યુ છે (સેલ અથવા સૂત્ર નથી). ફક્ત <emph>પૂર્ણાંક</emph> અથવા <emph>બાઇનરી</emph>  કરવા એક અથવા વધારે વેરિએબલને પસંદ કરી શકો છો."
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