{"id":"W4285099531","doi":"10.18280/jesa.550306","title":"Artificial Techniques Based on Neural Network and Fuzzy Logic Combination Approach for Avoiding Dynamic Obstacles","year":2022,"lang":"en","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Mosul","keywords":"Obstacle; Mobile robot; Obstacle avoidance; Robot; Fuzzy logic; Artificial neural network; Computer science; Artificial intelligence; Control theory (sociology); Simulation; Control engineering; Engineering; Control (management); Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003227791,0.0006348505,0.00053685,0.0007452452,0.0004430448,0.0004768705,0.0007438117,0.0005930012,0.001256157],"category_scores_gemma":[0.0005235189,0.0002942605,0.000531359,0.0005260577,0.0002742491,0.0005756925,0.0004163246,0.0005749472,0.0002121931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000417391,"about_ca_system_score_gemma":0.0006514461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005105168,"about_ca_topic_score_gemma":0.005890027,"domain_scores_codex":[0.9997955,0.00003557415,0.00001715409,0.00003501167,0.00009229934,0.00002448296],"domain_scores_gemma":[0.9998392,0.00006137628,0.00002005702,0.000009477626,0.00006262898,0.000007366639],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001238461,0.0001610141,0.00158065,0.0003706673,0.0001634075,0.0002693599,0.0001953028,0.5738936,0.01787397,0.01172191,0.002175893,0.3914704],"study_design_scores_gemma":[0.00001497417,0.0001237266,0.0004832149,0.00002815639,0.00003578968,0.0001075495,0.00002789603,0.9902661,0.002967537,0.003449425,0.002474619,0.00002099645],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0189313,0.000924639,0.9736466,0.0001188984,0.00007793844,0.00008257951,0.00002056084,0.0004167766,0.0057807],"genre_scores_gemma":[0.6226554,0.001502289,0.367949,0.0001474425,0.00007254116,0.0003506151,0.000105831,0.00004348497,0.00717343],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005105168,"threshold_uncertainty_score":0.01015091,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03218229702032457,"score_gpt":0.2686398953011813,"score_spread":0.2364575982808567,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}